{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}/Users/jasonbyers/Dropbox/Jason Byers/Co-Authored Projects/Projects with George Krause/Krause Projects/Confirmation Dynamics Project/Confirmation Delay & Senate Committees/2023 Version/Fall 2024/Statistics/Output/Committee Delay.APPENDIX G RESULTS.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}25 Dec 2024, 22:01:10
{txt}
{com}. 
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. **** JSB UPDATED DATABASE: ADDING EXECUTIVE NOMINATION POSITIONS COVERED IN OSTRANDER DATABASE FROM MAY 2012 THROUGH DECEMBER 2020 AND UPDATING ALL OTHER DATA [SUMMER/FALL 2023]: /// 
> *** ADDITIONAL VARIABLES ADDED IN MARCH 2024 IN RESPSONSE TO LSQ REFEREE REPORTS ****
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. **** "EXECUTIVE DEFERENCE OR LEGISLATIVE CONSTRAINT? COMMITTEE FOUNDATIONS OF CONFIRMATION DELAY FOR U.S. EXECUTIVE BRANCH APPOINTMENTS" [KRAUSE & BYERS] ****
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. **** APPENDIX G SENSITIVITY ANALYSES: EVALUATING DIFFERENCES IN REPORTED MANUSCRIPT MODELS 1-4 BASED ON WHETHER EXECUTIVE NOMINEE WAS RECENTLY SENATE CONFIRMED IN PRIOR TWO CONGRESSES [PRIORCONFIRM==1] OR HAD NOT BEEN [PRIORCONFIRM==0] ****
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. **** RATIONALE: THOSE WHO WERE NOT PRIOR SENATE CONFIRMED SHOULD FACE LONGER COMMITTEE CONFIRMATION DELAY THAN THOSE WHO WERE CONFIRMED WITHIN THE PRIOR TWO CONGRESSES *** 
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. *** COMMITTEE CONTROL COVARIATES:       experience_median  / chair_experience_1; ///
> ***                                                                             ln_combills_workload; committeestaffsize [# Committee Staff]   
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. *** OSTRANDER CONTROL COVARIATES:       sendivide  polarization pres_app_m first90 preselection lameduck workload [Executive Civilian Nominations: Senate] 
. ***                                                                             female priorconfirm _Itier_2 _Itier_3 _Itier_4 defense infrastructure social
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. *** ADDITIONAL CONTROL COVARIATES:      pressenfloorabsdist [-] [|Senate Floor Median - President|]; kv_workload (# civilian executive nominations made in a given year/session)        
. ***                                                                             denied [-] [nominee previously denied in same Congress]; fvra [+] [= 1 if subject to FVRA 1998, = 0 otherwise]; 
. ***                                                                             firstrecess[-] [= 1 is nominated in July or August affected by August Recess, = 0 otherwise]; 
. ***                                                                     secondrecess [-] [= 1 is nominated in November or December affected by December Recess, = 0 otherwise]; major policy agency binary indicator [-];                      
. ***                                     committee-level & pressidential administration unit/fixed effects.
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.  * OPEN UPDATED "CONFIRMATION DELAY & SENATE COMMITTEES PROJECT" MANUSCRIPT DATABASE [12-23-2024] *
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. *use "C:\Users\gk57526\Dropbox\Confirmation Dynamics Project (Jason Byers)\Confirmation Delay & Senate Committees\2023 Version\Fall 2024\Statistics\Data\Committee Delay.MANUSCRIPT RESULTS.12-23-2024.dta", replace
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. use "/Users/jasonbyers/Dropbox/Jason Byers/Co-Authored Projects/Projects with George Krause/Krause Projects/Confirmation Dynamics Project/Confirmation Delay & Senate Committees/2023 Version/Fall 2024/Statistics/Data/Committee Delay.MANUSCRIPT RESULTS.12-23-2024.dta", replace
{txt}
{com}. 
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. *** EVALUATE PSCD HYPOTHESIS FOR MODELS PRESENTED IN MANUSCRIPT: DISTINCTION BETWEEN PRIOR CONFIRMATION (PRIORCONFIRM==1) VERSUS OTHERWISE (PRIORCONFIRM==0) ***
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. *** MODEL G.1A: FULL SAMPLE: |COMMITTEE MEDIAN - PRESIDENT| & PRIORCONFIRM==0 [COX SEMIPARAMETRIC MODEL] ***
. 
. stcox  c.committee_pres1##i.sendivide  pressenfloorabsdist   experience_median  committeestaffsize ln_combills_workload   pres_app_m first90 preselection lameduck   kv_workload  polarization   workload  female priorconfirm denied  x_itier_2 x_itier_3 x_itier_4 defense infrastructure social fvra firstrecess secondrecess policy_majagency  i.kbcom_1  i.presrev  if priorconfirm==0,  vce(cluster kbcom_1)

{col 9}{txt}Failure {bf:_d}: {res}confirmbinary
{col 3}{txt}Analysis time {bf:_t}: {res}legvetdur2plus1

{txt}note: {bf:priorconfirm} omitted because of collinearity.
Iteration 0:  Log pseudolikelihood = {res}-50063.777
{txt}Iteration 1:  Log pseudolikelihood = {res}-49906.291
{txt}Iteration 2:  Log pseudolikelihood = {res}-49283.565
{txt}Iteration 3:  Log pseudolikelihood = {res}-49231.464
{txt}Iteration 4:  Log pseudolikelihood = {res}-49230.199
{txt}Iteration 5:  Log pseudolikelihood = {res}-49230.198
{txt}Refining estimates:
Iteration 0:  Log pseudolikelihood = {res}-49230.198

{txt}Cox regression with Breslow method for ties

No. of subjects = {res}{ralign 7:8,398}{col 54}{txt}{lalign 13:Number of obs} = {res}{ralign 9:8,398}
{txt}No. of failures = {res}{ralign 7:6,054}
{txt}Time at risk    = {res}{ralign 7:828,365}
{col 54}{txt}{lalign 13:Wald chi2({res:19})} = {res}{ralign 9:112366.19}
{txt}Log pseudolikelihood = {res}-49230.198{col 54}{txt}{lalign 13:Prob > chi2} = {res}{ralign 9:0.0000}

{txt}{ralign 81:(Std. err. adjusted for {res:20} clusters in {res:kbcom_1})}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}             _t{col 17}{c |} Haz. ratio{col 29}   std. err.{col 41}      z{col 49}   P>|z|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
committee_pres1 {c |}{col 17}{res}{space 2} .3930544{col 29}{space 2} .2240938{col 40}{space 1}   -1.64{col 49}{space 3}0.101{col 57}{space 4} .1285741{col 70}{space 3} 1.201578
{txt}{space 4}1.sendivide {c |}{col 17}{res}{space 2} .2979251{col 29}{space 2} .1623134{col 40}{space 1}   -2.22{col 49}{space 3}0.026{col 57}{space 4} .1024145{col 70}{space 3} .8666678
{txt}{space 15} {c |}
{space 6}sendivide#{c |}
{space 13}c. {c |}
committee_pres1 {c |}
{space 13}1  {c |}{col 17}{res}{space 2} 4.870389{col 29}{space 2} 3.365768{col 40}{space 1}    2.29{col 49}{space 3}0.022{col 57}{space 4} 1.256973{col 70}{space 3} 18.87129
{txt}{space 15} {c |}
pressenfloora~t {c |}{col 17}{res}{space 2} 1.123247{col 29}{space 2} .7990169{col 40}{space 1}    0.16{col 49}{space 3}0.870{col 57}{space 4}  .278597{col 70}{space 3} 4.528703
{txt}experience_me~n {c |}{col 17}{res}{space 2} .9919995{col 29}{space 2} .0115781{col 40}{space 1}   -0.69{col 49}{space 3}0.491{col 57}{space 4} .9695645{col 70}{space 3} 1.014954
{txt}committeestaf~e {c |}{col 17}{res}{space 2}   .99211{col 29}{space 2} .0043102{col 40}{space 1}   -1.82{col 49}{space 3}0.068{col 57}{space 4}  .983698{col 70}{space 3} 1.000594
{txt}ln_combills_w~d {c |}{col 17}{res}{space 2} .8583902{col 29}{space 2} .0813829{col 40}{space 1}   -1.61{col 49}{space 3}0.107{col 57}{space 4} .7128258{col 70}{space 3}  1.03368
{txt}{space 5}pres_app_m {c |}{col 17}{res}{space 2} 1.003617{col 29}{space 2} .0024085{col 40}{space 1}    1.50{col 49}{space 3}0.132{col 57}{space 4} .9989072{col 70}{space 3} 1.008348
{txt}{space 8}first90 {c |}{col 17}{res}{space 2} 2.927928{col 29}{space 2} .2822888{col 40}{space 1}   11.14{col 49}{space 3}0.000{col 57}{space 4} 2.423784{col 70}{space 3} 3.536933
{txt}{space 3}preselection {c |}{col 17}{res}{space 2} .7206569{col 29}{space 2} .0501527{col 40}{space 1}   -4.71{col 49}{space 3}0.000{col 57}{space 4} .6287686{col 70}{space 3} .8259739
{txt}{space 7}lameduck {c |}{col 17}{res}{space 2} .8388008{col 29}{space 2}  .062679{col 40}{space 1}   -2.35{col 49}{space 3}0.019{col 57}{space 4} .7245247{col 70}{space 3} .9711012
{txt}{space 4}kv_workload {c |}{col 17}{res}{space 2}        1{col 29}{space 2} .0000327{col 40}{space 1}    0.01{col 49}{space 3}0.990{col 57}{space 4} .9999363{col 70}{space 3} 1.000064
{txt}{space 3}polarization {c |}{col 17}{res}{space 2} .0382418{col 29}{space 2} .0508786{col 40}{space 1}   -2.45{col 49}{space 3}0.014{col 57}{space 4} .0028188{col 70}{space 3} .5188187
{txt}{space 7}workload {c |}{col 17}{res}{space 2} 1.002008{col 29}{space 2} .0015673{col 40}{space 1}    1.28{col 49}{space 3}0.200{col 57}{space 4} .9989412{col 70}{space 3} 1.005085
{txt}{space 9}female {c |}{col 17}{res}{space 2} .9922035{col 29}{space 2} .0426494{col 40}{space 1}   -0.18{col 49}{space 3}0.856{col 57}{space 4} .9120365{col 70}{space 3} 1.079417
{txt}{space 3}priorconfirm {c |}{col 17}{res}{space 2}        1{col 29}{txt}  (omitted)
{space 9}denied {c |}{col 17}{res}{space 2}  .670341{col 29}{space 2} .0703481{col 40}{space 1}   -3.81{col 49}{space 3}0.000{col 57}{space 4}  .545717{col 70}{space 3}  .823425
{txt}{space 6}x_itier_2 {c |}{col 17}{res}{space 2} .9708151{col 29}{space 2} .0469445{col 40}{space 1}   -0.61{col 49}{space 3}0.540{col 57}{space 4} .8830312{col 70}{space 3} 1.067326
{txt}{space 6}x_itier_3 {c |}{col 17}{res}{space 2} .8460067{col 29}{space 2} .1637018{col 40}{space 1}   -0.86{col 49}{space 3}0.387{col 57}{space 4} .5789843{col 70}{space 3} 1.236177
{txt}{space 6}x_itier_4 {c |}{col 17}{res}{space 2} .8328791{col 29}{space 2} .1092075{col 40}{space 1}   -1.39{col 49}{space 3}0.163{col 57}{space 4} .6441279{col 70}{space 3} 1.076941
{txt}{space 8}defense {c |}{col 17}{res}{space 2} .9980639{col 29}{space 2} .0794776{col 40}{space 1}   -0.02{col 49}{space 3}0.981{col 57}{space 4} .8538383{col 70}{space 3} 1.166651
{txt}{space 1}infrastructure {c |}{col 17}{res}{space 2} .9707591{col 29}{space 2} .0846716{col 40}{space 1}   -0.34{col 49}{space 3}0.734{col 57}{space 4} .8182159{col 70}{space 3} 1.151741
{txt}{space 9}social {c |}{col 17}{res}{space 2} .9242802{col 29}{space 2} .0647341{col 40}{space 1}   -1.12{col 49}{space 3}0.261{col 57}{space 4} .8057268{col 70}{space 3} 1.060277
{txt}{space 11}fvra {c |}{col 17}{res}{space 2} 1.209515{col 29}{space 2} .0823414{col 40}{space 1}    2.79{col 49}{space 3}0.005{col 57}{space 4} 1.058432{col 70}{space 3} 1.382163
{txt}{space 4}firstrecess {c |}{col 17}{res}{space 2} .9648626{col 29}{space 2} .0436559{col 40}{space 1}   -0.79{col 49}{space 3}0.429{col 57}{space 4} .8829828{col 70}{space 3} 1.054335
{txt}{space 3}secondrecess {c |}{col 17}{res}{space 2} .7432372{col 29}{space 2} .0628131{col 40}{space 1}   -3.51{col 49}{space 3}0.000{col 57}{space 4} .6297816{col 70}{space 3} .8771318
{txt}policy_majage~y {c |}{col 17}{res}{space 2} 1.273813{col 29}{space 2} .0857923{col 40}{space 1}    3.59{col 49}{space 3}0.000{col 57}{space 4} 1.116289{col 70}{space 3} 1.453566
{txt}{space 15} {c |}
{space 8}kbcom_1 {c |}
{space 13}2  {c |}{col 17}{res}{space 2} 1.122018{col 29}{space 2} .1417883{col 40}{space 1}    0.91{col 49}{space 3}0.362{col 57}{space 4} .8758589{col 70}{space 3} 1.437359
{txt}{space 13}3  {c |}{col 17}{res}{space 2} 1.042406{col 29}{space 2} .0832102{col 40}{space 1}    0.52{col 49}{space 3}0.603{col 57}{space 4} .8914348{col 70}{space 3} 1.218945
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 3.661608{col 29}{space 2} .4525687{col 40}{space 1}   10.50{col 49}{space 3}0.000{col 57}{space 4} 2.873854{col 70}{space 3} 4.665293
{txt}{space 13}5  {c |}{col 17}{res}{space 2} 1.435251{col 29}{space 2} .2544887{col 40}{space 1}    2.04{col 49}{space 3}0.042{col 57}{space 4} 1.013909{col 70}{space 3} 2.031688
{txt}{space 13}6  {c |}{col 17}{res}{space 2}  1.68332{col 29}{space 2} .2638664{col 40}{space 1}    3.32{col 49}{space 3}0.001{col 57}{space 4} 1.238049{col 70}{space 3} 2.288735
{txt}{space 13}7  {c |}{col 17}{res}{space 2}  1.21707{col 29}{space 2} .1247664{col 40}{space 1}    1.92{col 49}{space 3}0.055{col 57}{space 4} .9955329{col 70}{space 3} 1.487906
{txt}{space 13}8  {c |}{col 17}{res}{space 2} 1.097114{col 29}{space 2} .3278645{col 40}{space 1}    0.31{col 49}{space 3}0.756{col 57}{space 4} .6107678{col 70}{space 3} 1.970729
{txt}{space 13}9  {c |}{col 17}{res}{space 2} 1.108197{col 29}{space 2} .1481093{col 40}{space 1}    0.77{col 49}{space 3}0.442{col 57}{space 4} .8528145{col 70}{space 3} 1.440055
{txt}{space 12}10  {c |}{col 17}{res}{space 2} .8395156{col 29}{space 2} .2096076{col 40}{space 1}   -0.70{col 49}{space 3}0.484{col 57}{space 4} .5146399{col 70}{space 3} 1.369475
{txt}{space 12}11  {c |}{col 17}{res}{space 2}  1.35022{col 29}{space 2} .3635217{col 40}{space 1}    1.12{col 49}{space 3}0.265{col 57}{space 4} .7965888{col 70}{space 3} 2.288625
{txt}{space 12}12  {c |}{col 17}{res}{space 2} 1.317559{col 29}{space 2} .4785732{col 40}{space 1}    0.76{col 49}{space 3}0.448{col 57}{space 4} .6465328{col 70}{space 3} 2.685033
{txt}{space 12}13  {c |}{col 17}{res}{space 2} .7483034{col 29}{space 2} .0798739{col 40}{space 1}   -2.72{col 49}{space 3}0.007{col 57}{space 4} .6070444{col 70}{space 3} .9224334
{txt}{space 12}14  {c |}{col 17}{res}{space 2} 1.206228{col 29}{space 2} .2609095{col 40}{space 1}    0.87{col 49}{space 3}0.386{col 57}{space 4} .7894285{col 70}{space 3} 1.843088
{txt}{space 12}15  {c |}{col 17}{res}{space 2}  2.02911{col 29}{space 2} .8166557{col 40}{space 1}    1.76{col 49}{space 3}0.079{col 57}{space 4} .9219823{col 70}{space 3}  4.46569
{txt}{space 12}16  {c |}{col 17}{res}{space 2} 1.390833{col 29}{space 2} .4307856{col 40}{space 1}    1.07{col 49}{space 3}0.287{col 57}{space 4} .7579324{col 70}{space 3} 2.552228
{txt}{space 12}17  {c |}{col 17}{res}{space 2} .6596885{col 29}{space 2} .0984417{col 40}{space 1}   -2.79{col 49}{space 3}0.005{col 57}{space 4} .4924009{col 70}{space 3} .8838103
{txt}{space 12}18  {c |}{col 17}{res}{space 2} .6696927{col 29}{space 2} .1816965{col 40}{space 1}   -1.48{col 49}{space 3}0.139{col 57}{space 4} .3934897{col 70}{space 3} 1.139771
{txt}{space 12}19  {c |}{col 17}{res}{space 2} .5421556{col 29}{space 2} .0630377{col 40}{space 1}   -5.27{col 49}{space 3}0.000{col 57}{space 4} .4316709{col 70}{space 3} .6809186
{txt}{space 12}20  {c |}{col 17}{res}{space 2} .9461994{col 29}{space 2} .0896062{col 40}{space 1}   -0.58{col 49}{space 3}0.559{col 57}{space 4} .7859101{col 70}{space 3}  1.13918
{txt}{space 15} {c |}
{space 8}presrev {c |}
{space 13}2  {c |}{col 17}{res}{space 2} 1.636011{col 29}{space 2} .3407097{col 40}{space 1}    2.36{col 49}{space 3}0.018{col 57}{space 4} 1.087722{col 70}{space 3} 2.460675
{txt}{space 13}3  {c |}{col 17}{res}{space 2} 1.676824{col 29}{space 2} .5051864{col 40}{space 1}    1.72{col 49}{space 3}0.086{col 57}{space 4} .9290541{col 70}{space 3} 3.026452
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 1.612521{col 29}{space 2} .4237677{col 40}{space 1}    1.82{col 49}{space 3}0.069{col 57}{space 4}   .96341{col 70}{space 3}  2.69898
{txt}{space 13}5  {c |}{col 17}{res}{space 2} 1.207739{col 29}{space 2} .4474033{col 40}{space 1}    0.51{col 49}{space 3}0.610{col 57}{space 4}  .584316{col 70}{space 3} 2.496308
{txt}{space 13}6  {c |}{col 17}{res}{space 2}  1.02983{col 29}{space 2} .4695288{col 40}{space 1}    0.06{col 49}{space 3}0.949{col 57}{space 4} .4213844{col 70}{space 3} 2.516822
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. 
. * DESCRIPTIVE STATISTICS FOR EACH PARTISAN CONTROL REGIME [NOTE: THESE VARY ACROSS SUBSAMPLES OF INTEREST] *
. sum wSenComm_committee_pres1 if e(sample) & sendivide==0, detail

                  {txt}wSenComm_committee_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}-.5386078      -.5386078
{txt} 5%    {res}-.4976805      -.5386078
{txt}10%    {res} -.412061      -.5386078       {txt}Obs         {res}      4,475
{txt}25%    {res}-.3707183      -.5386078       {txt}Sum of wgt. {res}      4,475

{txt}50%    {res}-.2758437                      {txt}Mean          {res}-.1949483
                        {txt}Largest       Std. dev.     {res} .2310165
{txt}75%    {res}-.0624062        .490939
{txt}90%    {res} .1603195        .490939       {txt}Variance      {res} .0533686
{txt}95%    {res} .2121217        .490939       {txt}Skewness      {res} .8403455
{txt}99%    {res} .4655938        .490939       {txt}Kurtosis      {res} 2.951248
{txt}
{com}. sum wSenComm_committee_pres1 if e(sample) & sendivide==1, detail

                  {txt}wSenComm_committee_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}-.1966079      -.5386078
{txt} 5%    {res} -.115061      -.2201461
{txt}10%    {res}-.0252148      -.1966079       {txt}Obs         {res}      3,923
{txt}25%    {res} .0905807      -.1966079       {txt}Sum of wgt. {res}      3,923

{txt}50%    {res} .2273195                      {txt}Mean          {res} .2177173
                        {txt}Largest       Std. dev.     {res} .1758748
{txt}75%    {res} .3489552        .490939
{txt}90%    {res} .4655938        .490939       {txt}Variance      {res}  .030932
{txt}95%    {res}  .490939        .490939       {txt}Skewness      {res}-.4540304
{txt}99%    {res}  .490939        .676923       {txt}Kurtosis      {res} 2.835072
{txt}
{com}. 
. 
. 
. ** CONDITIONAL COEFFICIENT ANALYSIS TESTS: DIRECTION [+] ** 
. 
. * DIFFERENCE BETWEEN DIVIDED AND UNIFIED PARTISAN CONTROL OF SENATE & PRESIDENCY: INTERQUARTILE UNIT CHANGE IN "wSenComm_committee_pres1"  *
. lincomest (committee_pres1 * 0.3083121 +  1.sendivide#c.committee_pres1 * 0.2583745) - committee_pres1 * 0.3083121, eform(hr)
{txt}Confidence interval for formula:
{res}(committee_pres1*0.3083121+1.sendivide#c.committee_pres1*0.2583745)-committee_pres1*0.3083121

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}  1.50539{col 26}{space 2} .2687937{col 37}{space 1}    2.29{col 46}{space 3}0.022{col 54}{space 4} 1.060873{col 67}{space 3} 2.136164
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix model1a = r(table)
{txt}
{com}. mat list model1a
{res}
{txt}model1a[9,1]
               (1)
     b {res} 1.5053896
{txt}    se {res} .26879371
{txt}     z {res} 2.2909104
{txt}pvalue {res}  .0219686
{txt}    ll {res} 1.0608727
{txt}    ul {res} 2.1361639
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         1
{reset}
{com}. 
. *
. *
. *
. *
. 
. 
. 
. *** MODEL G.1B: FULL SAMPLE: |COMMITTEE MEDIAN - PRESIDENT| & PRIORCONFIRM==1 [COX SEMIPARAMETRIC MODEL] ***
. 
. stcox  c.committee_pres1##i.sendivide  pressenfloorabsdist   chair_experience_1  committeestaffsize ln_combills_workload   pres_app_m first90 preselection lameduck   kv_workload  polarization   workload  female priorconfirm denied  x_itier_2 x_itier_3 x_itier_4 defense infrastructure social fvra firstrecess secondrecess policy_majagency   i.kbcom_1  i.presrev  if priorconfirm==1,  vce(cluster kbcom_1)

{col 9}{txt}Failure {bf:_d}: {res}confirmbinary
{col 3}{txt}Analysis time {bf:_t}: {res}legvetdur2plus1

{txt}note: {bf:priorconfirm} omitted because of collinearity.
Iteration 0:  Log pseudolikelihood = {res}  -6710.12
{txt}Iteration 1:  Log pseudolikelihood = {res}-6597.8262
{txt}Iteration 2:  Log pseudolikelihood = {res}-6567.6773
{txt}Iteration 3:  Log pseudolikelihood = {res}-6565.4038
{txt}Iteration 4:  Log pseudolikelihood = {res}-6565.3326
{txt}Iteration 5:  Log pseudolikelihood = {res}-6565.3198
{txt}Iteration 6:  Log pseudolikelihood = {res}-6565.3151
{txt}Iteration 7:  Log pseudolikelihood = {res}-6565.3133
{txt}Iteration 8:  Log pseudolikelihood = {res}-6565.3127
{txt}Iteration 9:  Log pseudolikelihood = {res}-6565.3124
{txt}Iteration 10: Log pseudolikelihood = {res}-6565.3124
{txt}Iteration 11: Log pseudolikelihood = {res}-6565.3123
{txt}Iteration 12: Log pseudolikelihood = {res}-6565.3123
{txt}Iteration 13: Log pseudolikelihood = {res}-6565.3123
{txt}Iteration 14: Log pseudolikelihood = {res}-6565.3123
{txt}Iteration 15: Log pseudolikelihood = {res}-6565.3123
{txt}Iteration 16: Log pseudolikelihood = {res}-6565.3123
{txt}Iteration 17: Log pseudolikelihood = {res}-6565.3123
{txt}Iteration 18: Log pseudolikelihood = {res}-6565.3123
{txt}Iteration 19: Log pseudolikelihood = {res}-6565.3123
{txt}Iteration 20: Log pseudolikelihood = {res}-6565.3123
{txt}Iteration 21: Log pseudolikelihood = {res}-6565.3123
{txt}Iteration 22: Log pseudolikelihood = {res}-6565.3123
{txt}Iteration 23: Log pseudolikelihood = {res}-6565.3123
{txt}Iteration 24: Log pseudolikelihood = {res}-6565.3123
{txt}Iteration 25: Log pseudolikelihood = {res}-6565.3123
{txt}Iteration 26: Log pseudolikelihood = {res}-6565.3123
{txt}Iteration 27: Log pseudolikelihood = {res}-6565.3123
{txt}Refining estimates:
Iteration 0:  Log pseudolikelihood = {res}-6565.3123
{txt}Iteration 1:  Log pseudolikelihood = {res}-6565.3123
{txt}Iteration 2:  Log pseudolikelihood = {res}-6565.3123
{txt}Iteration 3:  Log pseudolikelihood = {res}-6565.3123

{txt}Cox regression with Breslow method for ties

No. of subjects = {res}{ralign 7:1,481}{col 55}{txt}{lalign 13:Number of obs} = {res}{ralign 8:1,481}
{txt}No. of failures = {res}{ralign 7:1,022}
{txt}Time at risk    = {res}{ralign 7:159,446}
{col 55}{txt}{lalign 13:Wald chi2({res:19})} = {res}{ralign 8:10338.41}
{txt}Log pseudolikelihood = {res}-6565.3123{col 55}{txt}{lalign 13:Prob > chi2} = {res}{ralign 8:0.0000}

{txt}{ralign 81:(Std. err. adjusted for {res:20} clusters in {res:kbcom_1})}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}             _t{col 17}{c |} Haz. ratio{col 29}   std. err.{col 41}      z{col 49}   P>|z|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
committee_pres1 {c |}{col 17}{res}{space 2} .2116576{col 29}{space 2}  .137345{col 40}{space 1}   -2.39{col 49}{space 3}0.017{col 57}{space 4} .0593318{col 70}{space 3} .7550578
{txt}{space 4}1.sendivide {c |}{col 17}{res}{space 2} .3252125{col 29}{space 2}  .145789{col 40}{space 1}   -2.51{col 49}{space 3}0.012{col 57}{space 4} .1350776{col 70}{space 3} .7829808
{txt}{space 15} {c |}
{space 6}sendivide#{c |}
{space 13}c. {c |}
committee_pres1 {c |}
{space 13}1  {c |}{col 17}{res}{space 2} 3.785142{col 29}{space 2}  1.34089{col 40}{space 1}    3.76{col 49}{space 3}0.000{col 57}{space 4} 1.890354{col 70}{space 3} 7.579162
{txt}{space 15} {c |}
pressenfloora~t {c |}{col 17}{res}{space 2} 1.879792{col 29}{space 2} 1.830814{col 40}{space 1}    0.65{col 49}{space 3}0.517{col 57}{space 4} .2786673{col 70}{space 3} 12.68041
{txt}chair_experie~1 {c |}{col 17}{res}{space 2} 1.013228{col 29}{space 2} .0050914{col 40}{space 1}    2.62{col 49}{space 3}0.009{col 57}{space 4} 1.003298{col 70}{space 3} 1.023256
{txt}committeestaf~e {c |}{col 17}{res}{space 2} .9888792{col 29}{space 2} .0049493{col 40}{space 1}   -2.23{col 49}{space 3}0.025{col 57}{space 4} .9792261{col 70}{space 3} .9986275
{txt}ln_combills_w~d {c |}{col 17}{res}{space 2}   1.0752{col 29}{space 2} .1816958{col 40}{space 1}    0.43{col 49}{space 3}0.668{col 57}{space 4} .7720521{col 70}{space 3}  1.49738
{txt}{space 5}pres_app_m {c |}{col 17}{res}{space 2} .9975565{col 29}{space 2} .0055486{col 40}{space 1}   -0.44{col 49}{space 3}0.660{col 57}{space 4} .9867406{col 70}{space 3} 1.008491
{txt}{space 8}first90 {c |}{col 17}{res}{space 2} 1.727926{col 29}{space 2} .2998891{col 40}{space 1}    3.15{col 49}{space 3}0.002{col 57}{space 4} 1.229689{col 70}{space 3} 2.428035
{txt}{space 3}preselection {c |}{col 17}{res}{space 2} .6066461{col 29}{space 2} .0622547{col 40}{space 1}   -4.87{col 49}{space 3}0.000{col 57}{space 4} .4961171{col 70}{space 3} .7417996
{txt}{space 7}lameduck {c |}{col 17}{res}{space 2} 1.142888{col 29}{space 2} .1029656{col 40}{space 1}    1.48{col 49}{space 3}0.138{col 57}{space 4} .9578929{col 70}{space 3} 1.363611
{txt}{space 4}kv_workload {c |}{col 17}{res}{space 2} .9999853{col 29}{space 2} .0000484{col 40}{space 1}   -0.30{col 49}{space 3}0.762{col 57}{space 4} .9998904{col 70}{space 3}  1.00008
{txt}{space 3}polarization {c |}{col 17}{res}{space 2} .0117105{col 29}{space 2} .0238467{col 40}{space 1}   -2.18{col 49}{space 3}0.029{col 57}{space 4} .0002164{col 70}{space 3} .6337475
{txt}{space 7}workload {c |}{col 17}{res}{space 2} 1.001715{col 29}{space 2} .0014967{col 40}{space 1}    1.15{col 49}{space 3}0.252{col 57}{space 4} .9987856{col 70}{space 3} 1.004652
{txt}{space 9}female {c |}{col 17}{res}{space 2}  1.04605{col 29}{space 2} .0859478{col 40}{space 1}    0.55{col 49}{space 3}0.584{col 57}{space 4} .8904591{col 70}{space 3} 1.228826
{txt}{space 3}priorconfirm {c |}{col 17}{res}{space 2}        1{col 29}{txt}  (omitted)
{space 9}denied {c |}{col 17}{res}{space 2} .6011166{col 29}{space 2} .0964065{col 40}{space 1}   -3.17{col 49}{space 3}0.002{col 57}{space 4} .4389792{col 70}{space 3} .8231398
{txt}{space 6}x_itier_2 {c |}{col 17}{res}{space 2} .8731591{col 29}{space 2} .0909056{col 40}{space 1}   -1.30{col 49}{space 3}0.193{col 57}{space 4} .7119899{col 70}{space 3} 1.070811
{txt}{space 6}x_itier_3 {c |}{col 17}{res}{space 2} .6650724{col 29}{space 2} .1246481{col 40}{space 1}   -2.18{col 49}{space 3}0.030{col 57}{space 4} .4606133{col 70}{space 3} .9602879
{txt}{space 6}x_itier_4 {c |}{col 17}{res}{space 2}  .671268{col 29}{space 2} .0611854{col 40}{space 1}   -4.37{col 49}{space 3}0.000{col 57}{space 4} .5614484{col 70}{space 3} .8025685
{txt}{space 8}defense {c |}{col 17}{res}{space 2} 1.032087{col 29}{space 2} .1565332{col 40}{space 1}    0.21{col 49}{space 3}0.835{col 57}{space 4} .7666854{col 70}{space 3} 1.389361
{txt}{space 1}infrastructure {c |}{col 17}{res}{space 2} .8460778{col 29}{space 2} .1291509{col 40}{space 1}   -1.09{col 49}{space 3}0.274{col 57}{space 4} .6273028{col 70}{space 3} 1.141152
{txt}{space 9}social {c |}{col 17}{res}{space 2} .9198641{col 29}{space 2} .1461581{col 40}{space 1}   -0.53{col 49}{space 3}0.599{col 57}{space 4} .6737138{col 70}{space 3} 1.255949
{txt}{space 11}fvra {c |}{col 17}{res}{space 2} 1.076638{col 29}{space 2} .1444761{col 40}{space 1}    0.55{col 49}{space 3}0.582{col 57}{space 4} .8276478{col 70}{space 3} 1.400536
{txt}{space 4}firstrecess {c |}{col 17}{res}{space 2} .9514327{col 29}{space 2} .1043808{col 40}{space 1}   -0.45{col 49}{space 3}0.650{col 57}{space 4} .7673501{col 70}{space 3} 1.179676
{txt}{space 3}secondrecess {c |}{col 17}{res}{space 2} .7932329{col 29}{space 2} .1007727{col 40}{space 1}   -1.82{col 49}{space 3}0.068{col 57}{space 4} .6183917{col 70}{space 3} 1.017508
{txt}policy_majage~y {c |}{col 17}{res}{space 2} 1.106028{col 29}{space 2} .1086676{col 40}{space 1}    1.03{col 49}{space 3}0.305{col 57}{space 4} .9122947{col 70}{space 3} 1.340902
{txt}{space 15} {c |}
{space 8}kbcom_1 {c |}
{space 13}2  {c |}{col 17}{res}{space 2} .5904796{col 29}{space 2} .0896174{col 40}{space 1}   -3.47{col 49}{space 3}0.001{col 57}{space 4} .4385485{col 70}{space 3}  .795046
{txt}{space 13}3  {c |}{col 17}{res}{space 2} .5443285{col 29}{space 2} .0285798{col 40}{space 1}  -11.58{col 49}{space 3}0.000{col 57}{space 4} .4910989{col 70}{space 3} .6033276
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 2.011682{col 29}{space 2} .5426034{col 40}{space 1}    2.59{col 49}{space 3}0.010{col 57}{space 4} 1.185681{col 70}{space 3} 3.413113
{txt}{space 13}5  {c |}{col 17}{res}{space 2}  .782577{col 29}{space 2} .1737013{col 40}{space 1}   -1.10{col 49}{space 3}0.269{col 57}{space 4} .5065168{col 70}{space 3} 1.209095
{txt}{space 13}6  {c |}{col 17}{res}{space 2} 1.039521{col 29}{space 2} .2072587{col 40}{space 1}    0.19{col 49}{space 3}0.846{col 57}{space 4} .7032689{col 70}{space 3} 1.536544
{txt}{space 13}7  {c |}{col 17}{res}{space 2} .6870774{col 29}{space 2} .0881794{col 40}{space 1}   -2.92{col 49}{space 3}0.003{col 57}{space 4} .5342722{col 70}{space 3} .8835857
{txt}{space 13}8  {c |}{col 17}{res}{space 2} .6517541{col 29}{space 2} .2391048{col 40}{space 1}   -1.17{col 49}{space 3}0.243{col 57}{space 4} .3175478{col 70}{space 3} 1.337699
{txt}{space 13}9  {c |}{col 17}{res}{space 2} .5098294{col 29}{space 2} .0641549{col 40}{space 1}   -5.35{col 49}{space 3}0.000{col 57}{space 4} .3983942{col 70}{space 3} .6524341
{txt}{space 12}10  {c |}{col 17}{res}{space 2}  .719273{col 29}{space 2} .1731064{col 40}{space 1}   -1.37{col 49}{space 3}0.171{col 57}{space 4} .4487829{col 70}{space 3} 1.152793
{txt}{space 12}11  {c |}{col 17}{res}{space 2} .7013516{col 29}{space 2} .2586441{col 40}{space 1}   -0.96{col 49}{space 3}0.336{col 57}{space 4} .3404318{col 70}{space 3} 1.444912
{txt}{space 12}12  {c |}{col 17}{res}{space 2} .8095969{col 29}{space 2} .2534511{col 40}{space 1}   -0.67{col 49}{space 3}0.500{col 57}{space 4} .4383217{col 70}{space 3} 1.495356
{txt}{space 12}13  {c |}{col 17}{res}{space 2} .3268777{col 29}{space 2} .0654164{col 40}{space 1}   -5.59{col 49}{space 3}0.000{col 57}{space 4} .2208201{col 70}{space 3} .4838737
{txt}{space 12}14  {c |}{col 17}{res}{space 2} .7093015{col 29}{space 2} .3444771{col 40}{space 1}   -0.71{col 49}{space 3}0.479{col 57}{space 4} .2738036{col 70}{space 3}  1.83748
{txt}{space 12}15  {c |}{col 17}{res}{space 2} .7474146{col 29}{space 2} .3042998{col 40}{space 1}   -0.72{col 49}{space 3}0.475{col 57}{space 4} .3365164{col 70}{space 3} 1.660034
{txt}{space 12}16  {c |}{col 17}{res}{space 2} .6938544{col 29}{space 2} .2095999{col 40}{space 1}   -1.21{col 49}{space 3}0.226{col 57}{space 4} .3838283{col 70}{space 3} 1.254295
{txt}{space 12}17  {c |}{col 17}{res}{space 2} .4990075{col 29}{space 2} .0599819{col 40}{space 1}   -5.78{col 49}{space 3}0.000{col 57}{space 4} .3942671{col 70}{space 3} .6315731
{txt}{space 12}18  {c |}{col 17}{res}{space 2} 1.955661{col 29}{space 2} .7807323{col 40}{space 1}    1.68{col 49}{space 3}0.093{col 57}{space 4} .8942931{col 70}{space 3} 4.276686
{txt}{space 12}19  {c |}{col 17}{res}{space 2} 6.85e-14{col 29}{space 2} 7.21e-14{col 40}{space 1}  -28.77{col 49}{space 3}0.000{col 57}{space 4} 8.68e-15{col 70}{space 3} 5.40e-13
{txt}{space 12}20  {c |}{col 17}{res}{space 2} .4862039{col 29}{space 2} .0991323{col 40}{space 1}   -3.54{col 49}{space 3}0.000{col 57}{space 4} .3260368{col 70}{space 3}  .725054
{txt}{space 15} {c |}
{space 8}presrev {c |}
{space 13}2  {c |}{col 17}{res}{space 2} 2.054617{col 29}{space 2} .5975964{col 40}{space 1}    2.48{col 49}{space 3}0.013{col 57}{space 4} 1.161862{col 70}{space 3} 3.633352
{txt}{space 13}3  {c |}{col 17}{res}{space 2} 1.872514{col 29}{space 2} .7009069{col 40}{space 1}    1.68{col 49}{space 3}0.094{col 57}{space 4} .8991023{col 70}{space 3} 3.899789
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 1.389927{col 29}{space 2} .9003826{col 40}{space 1}    0.51{col 49}{space 3}0.611{col 57}{space 4}  .390473{col 70}{space 3} 4.947581
{txt}{space 13}5  {c |}{col 17}{res}{space 2} 1.000439{col 29}{space 2} .4697176{col 40}{space 1}    0.00{col 49}{space 3}0.999{col 57}{space 4} .3986038{col 70}{space 3} 2.510958
{txt}{space 13}6  {c |}{col 17}{res}{space 2} 1.249416{col 29}{space 2}  .832111{col 40}{space 1}    0.33{col 49}{space 3}0.738{col 57}{space 4} .3386936{col 70}{space 3} 4.609006
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. 
. * DESCRIPTIVE STATISTICS FOR EACH PARTISAN CONTROL REGIME [NOTE: THESE VARY ACROSS SUBSAMPLES OF INTEREST] *
. sum wSenComm_committee_pres1 if e(sample) & sendivide==0, detail

                  {txt}wSenComm_committee_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}-.5386078      -.5386078
{txt} 5%    {res} -.412061      -.5386078
{txt}10%    {res}-.4026805      -.5386078       {txt}Obs         {res}        713
{txt}25%    {res}-.3220448      -.5386078       {txt}Sum of wgt. {res}        713

{txt}50%    {res} -.132869                      {txt}Mean          {res}-.1219668
                        {txt}Largest       Std. dev.     {res} .2250392
{txt}75%    {res} .1149552       .3563195
{txt}90%    {res} .1603195       .3563195       {txt}Variance      {res} .0506426
{txt}95%    {res} .2121217       .3563195       {txt}Skewness      {res} .2151789
{txt}99%    {res} .3387852       .4655938       {txt}Kurtosis      {res} 1.889663
{txt}
{com}. sum wSenComm_committee_pres1 if e(sample) & sendivide==1, detail

                  {txt}wSenComm_committee_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}-.1966079      -.2916805
{txt} 5%    {res}-.1966079      -.1966079
{txt}10%    {res}-.0977183      -.1966079       {txt}Obs         {res}        768
{txt}25%    {res} .0419552      -.1966079       {txt}Sum of wgt. {res}        768

{txt}50%    {res} .1929552                      {txt}Mean          {res} .1588885
                        {txt}Largest       Std. dev.     {res} .1837394
{txt}75%    {res} .2885807        .490939
{txt}90%    {res} .3931217        .490939       {txt}Variance      {res} .0337602
{txt}95%    {res} .4655938        .490939       {txt}Skewness      {res}-.1952754
{txt}99%    {res} .4706168        .490939       {txt}Kurtosis      {res} 2.343359
{txt}
{com}. 
. 
. 
. ** CONDITIONAL COEFFICIENT ANALYSIS TESTS: DIRECTION [+] ** 
. 
. * DIFFERENCE BETWEEN DIVIDED AND UNIFIED PARTISAN CONTROL OF SENATE & PRESIDENCY: INTERQUARTILE UNIT CHANGE IN "wSenComm_committee_pres1"  *
. lincomest (committee_pres1 * 0.437 +  1.sendivide#c.committee_pres1 * 0.2466255) - committee_pres1 * 0.437, eform(hr)
{txt}Confidence interval for formula:
{res}(committee_pres1*0.437+1.sendivide#c.committee_pres1*0.2466255)-committee_pres1*0.437

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} 1.388576{col 26}{space 2} .1213162{col 37}{space 1}    3.76{col 46}{space 3}0.000{col 54}{space 4} 1.170045{col 67}{space 3} 1.647923
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix model1b = r(table)
{txt}
{com}. mat list model1b
{res}
{txt}model1b[9,1]
               (1)
     b {res} 1.3885764
{txt}    se {res} .12131623
{txt}     z {res} 3.7574575
{txt}pvalue {res} .00017165
{txt}    ll {res}  1.170045
{txt}    ul {res} 1.6479234
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         1
{reset}
{com}. 
. 
. 
. ******************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. 
. 
. 
. 
. *** MODEL G.2A: FULL SAMPLE: |COMMITTEE CHAIR - PRESIDENT| & PRIORCONFIRM==0 [COX SEMIPARAMETRIC MODEL] ***
. 
. stcox  c.chair_pres1##i.sendivide   pressenfloorabsdist   experience_median  committeestaffsize ln_combills_workload   pres_app_m first90 preselection lameduck   kv_workload  polarization   workload  female priorconfirm denied  x_itier_2 x_itier_3 x_itier_4 defense infrastructure social fvra firstrecess secondrecess policy_majagency   i.kbcom_1  i.presrev  if priorconfirm==0,  vce(cluster kbcom_1)

{col 9}{txt}Failure {bf:_d}: {res}confirmbinary
{col 3}{txt}Analysis time {bf:_t}: {res}legvetdur2plus1

{txt}note: {bf:priorconfirm} omitted because of collinearity.
Iteration 0:  Log pseudolikelihood = {res}-50063.777
{txt}Iteration 1:  Log pseudolikelihood = {res}-49902.682
{txt}Iteration 2:  Log pseudolikelihood = {res}-49284.383
{txt}Iteration 3:  Log pseudolikelihood = {res}-49232.956
{txt}Iteration 4:  Log pseudolikelihood = {res}-49231.719
{txt}Iteration 5:  Log pseudolikelihood = {res}-49231.717
{txt}Refining estimates:
Iteration 0:  Log pseudolikelihood = {res}-49231.717

{txt}Cox regression with Breslow method for ties

No. of subjects = {res}{ralign 7:8,398}{col 55}{txt}{lalign 13:Number of obs} = {res}{ralign 8:8,398}
{txt}No. of failures = {res}{ralign 7:6,054}
{txt}Time at risk    = {res}{ralign 7:828,365}
{col 55}{txt}{lalign 13:Wald chi2({res:19})} = {res}{ralign 8:49084.08}
{txt}Log pseudolikelihood = {res}-49231.717{col 55}{txt}{lalign 13:Prob > chi2} = {res}{ralign 8:0.0000}

{txt}{ralign 81:(Std. err. adjusted for {res:20} clusters in {res:kbcom_1})}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}             _t{col 17}{c |} Haz. ratio{col 29}   std. err.{col 41}      z{col 49}   P>|z|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}chair_pres1 {c |}{col 17}{res}{space 2} .8227159{col 29}{space 2} .2249038{col 40}{space 1}   -0.71{col 49}{space 3}0.475{col 57}{space 4} .4814587{col 70}{space 3} 1.405856
{txt}{space 4}1.sendivide {c |}{col 17}{res}{space 2} .3600468{col 29}{space 2} .1413476{col 40}{space 1}   -2.60{col 49}{space 3}0.009{col 57}{space 4} .1667989{col 70}{space 3} .7771855
{txt}{space 15} {c |}
{space 6}sendivide#{c |}
{space 2}c.chair_pres1 {c |}
{space 13}1  {c |}{col 17}{res}{space 2}  2.86699{col 29}{space 2} 1.243866{col 40}{space 1}    2.43{col 49}{space 3}0.015{col 57}{space 4} 1.224971{col 70}{space 3} 6.710066
{txt}{space 15} {c |}
pressenfloora~t {c |}{col 17}{res}{space 2} .6469196{col 29}{space 2} .4180771{col 40}{space 1}   -0.67{col 49}{space 3}0.500{col 57}{space 4} .1822865{col 70}{space 3} 2.295864
{txt}experience_me~n {c |}{col 17}{res}{space 2} .9957067{col 29}{space 2} .0115919{col 40}{space 1}   -0.37{col 49}{space 3}0.712{col 57}{space 4} .9732442{col 70}{space 3} 1.018688
{txt}committeestaf~e {c |}{col 17}{res}{space 2} .9929596{col 29}{space 2} .0044437{col 40}{space 1}   -1.58{col 49}{space 3}0.114{col 57}{space 4} .9842883{col 70}{space 3} 1.001707
{txt}ln_combills_w~d {c |}{col 17}{res}{space 2} .8237113{col 29}{space 2} .0788329{col 40}{space 1}   -2.03{col 49}{space 3}0.043{col 57}{space 4} .6828278{col 70}{space 3} .9936625
{txt}{space 5}pres_app_m {c |}{col 17}{res}{space 2} 1.003136{col 29}{space 2} .0023888{col 40}{space 1}    1.31{col 49}{space 3}0.189{col 57}{space 4} .9984652{col 70}{space 3} 1.007829
{txt}{space 8}first90 {c |}{col 17}{res}{space 2} 2.994614{col 29}{space 2} .2668911{col 40}{space 1}   12.31{col 49}{space 3}0.000{col 57}{space 4} 2.514656{col 70}{space 3} 3.566178
{txt}{space 3}preselection {c |}{col 17}{res}{space 2}  .708954{col 29}{space 2} .0470966{col 40}{space 1}   -5.18{col 49}{space 3}0.000{col 57}{space 4} .6224032{col 70}{space 3} .8075406
{txt}{space 7}lameduck {c |}{col 17}{res}{space 2} .8219844{col 29}{space 2} .0688325{col 40}{space 1}   -2.34{col 49}{space 3}0.019{col 57}{space 4} .6975646{col 70}{space 3} .9685962
{txt}{space 4}kv_workload {c |}{col 17}{res}{space 2} 1.000011{col 29}{space 2} .0000339{col 40}{space 1}    0.32{col 49}{space 3}0.747{col 57}{space 4} .9999444{col 70}{space 3} 1.000077
{txt}{space 3}polarization {c |}{col 17}{res}{space 2} .0253966{col 29}{space 2} .0350418{col 40}{space 1}   -2.66{col 49}{space 3}0.008{col 57}{space 4} .0016994{col 70}{space 3}  .379532
{txt}{space 7}workload {c |}{col 17}{res}{space 2} 1.001767{col 29}{space 2} .0015414{col 40}{space 1}    1.15{col 49}{space 3}0.251{col 57}{space 4}   .99875{col 70}{space 3} 1.004792
{txt}{space 9}female {c |}{col 17}{res}{space 2} .9889991{col 29}{space 2} .0438785{col 40}{space 1}   -0.25{col 49}{space 3}0.803{col 57}{space 4} .9066318{col 70}{space 3} 1.078849
{txt}{space 3}priorconfirm {c |}{col 17}{res}{space 2}        1{col 29}{txt}  (omitted)
{space 9}denied {c |}{col 17}{res}{space 2} .6664711{col 29}{space 2} .0714226{col 40}{space 1}   -3.79{col 49}{space 3}0.000{col 57}{space 4} .5402093{col 70}{space 3} .8222439
{txt}{space 6}x_itier_2 {c |}{col 17}{res}{space 2} .9566051{col 29}{space 2} .0496236{col 40}{space 1}   -0.86{col 49}{space 3}0.392{col 57}{space 4} .8641256{col 70}{space 3} 1.058982
{txt}{space 6}x_itier_3 {c |}{col 17}{res}{space 2} .8351097{col 29}{space 2} .1566627{col 40}{space 1}   -0.96{col 49}{space 3}0.337{col 57}{space 4} .5781787{col 70}{space 3} 1.206216
{txt}{space 6}x_itier_4 {c |}{col 17}{res}{space 2} .8324712{col 29}{space 2} .1095709{col 40}{space 1}   -1.39{col 49}{space 3}0.164{col 57}{space 4} .6431806{col 70}{space 3} 1.077471
{txt}{space 8}defense {c |}{col 17}{res}{space 2} 1.018482{col 29}{space 2} .0711324{col 40}{space 1}    0.26{col 49}{space 3}0.793{col 57}{space 4} .8881864{col 70}{space 3} 1.167892
{txt}{space 1}infrastructure {c |}{col 17}{res}{space 2} .9691314{col 29}{space 2} .0819945{col 40}{space 1}   -0.37{col 49}{space 3}0.711{col 57}{space 4} .8210427{col 70}{space 3}  1.14393
{txt}{space 9}social {c |}{col 17}{res}{space 2} .9392045{col 29}{space 2} .0714168{col 40}{space 1}   -0.82{col 49}{space 3}0.409{col 57}{space 4} .8091613{col 70}{space 3} 1.090148
{txt}{space 11}fvra {c |}{col 17}{res}{space 2} 1.216686{col 29}{space 2} .0838546{col 40}{space 1}    2.85{col 49}{space 3}0.004{col 57}{space 4} 1.062951{col 70}{space 3} 1.392656
{txt}{space 4}firstrecess {c |}{col 17}{res}{space 2} .9609367{col 29}{space 2} .0432069{col 40}{space 1}   -0.89{col 49}{space 3}0.376{col 57}{space 4} .8798769{col 70}{space 3} 1.049464
{txt}{space 3}secondrecess {c |}{col 17}{res}{space 2}  .747393{col 29}{space 2} .0607725{col 40}{space 1}   -3.58{col 49}{space 3}0.000{col 57}{space 4} .6372878{col 70}{space 3} .8765213
{txt}policy_majage~y {c |}{col 17}{res}{space 2} 1.277759{col 29}{space 2} .0845137{col 40}{space 1}    3.71{col 49}{space 3}0.000{col 57}{space 4} 1.122403{col 70}{space 3} 1.454619
{txt}{space 15} {c |}
{space 8}kbcom_1 {c |}
{space 13}2  {c |}{col 17}{res}{space 2} 1.086532{col 29}{space 2} .1300811{col 40}{space 1}    0.69{col 49}{space 3}0.488{col 57}{space 4} .8592818{col 70}{space 3} 1.373883
{txt}{space 13}3  {c |}{col 17}{res}{space 2} 1.067743{col 29}{space 2} .0899963{col 40}{space 1}    0.78{col 49}{space 3}0.437{col 57}{space 4} .9051524{col 70}{space 3} 1.259538
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 3.597411{col 29}{space 2} .4361441{col 40}{space 1}   10.56{col 49}{space 3}0.000{col 57}{space 4} 2.836559{col 70}{space 3} 4.562347
{txt}{space 13}5  {c |}{col 17}{res}{space 2} 1.450056{col 29}{space 2} .2560341{col 40}{space 1}    2.10{col 49}{space 3}0.035{col 57}{space 4} 1.025863{col 70}{space 3} 2.049652
{txt}{space 13}6  {c |}{col 17}{res}{space 2} 1.781884{col 29}{space 2} .2798866{col 40}{space 1}    3.68{col 49}{space 3}0.000{col 57}{space 4}  1.30972{col 70}{space 3} 2.424268
{txt}{space 13}7  {c |}{col 17}{res}{space 2} 1.261839{col 29}{space 2} .1303004{col 40}{space 1}    2.25{col 49}{space 3}0.024{col 57}{space 4}  1.03064{col 70}{space 3} 1.544902
{txt}{space 13}8  {c |}{col 17}{res}{space 2} 1.207735{col 29}{space 2} .3752747{col 40}{space 1}    0.61{col 49}{space 3}0.544{col 57}{space 4} .6568722{col 70}{space 3} 2.220558
{txt}{space 13}9  {c |}{col 17}{res}{space 2} 1.130165{col 29}{space 2} .1538529{col 40}{space 1}    0.90{col 49}{space 3}0.369{col 57}{space 4} .8654959{col 70}{space 3}  1.47577
{txt}{space 12}10  {c |}{col 17}{res}{space 2} .8479952{col 29}{space 2} .2219538{col 40}{space 1}   -0.63{col 49}{space 3}0.529{col 57}{space 4} .5076921{col 70}{space 3} 1.416401
{txt}{space 12}11  {c |}{col 17}{res}{space 2} 1.456677{col 29}{space 2} .4157819{col 40}{space 1}    1.32{col 49}{space 3}0.188{col 57}{space 4} .8325362{col 70}{space 3} 2.548726
{txt}{space 12}12  {c |}{col 17}{res}{space 2}  1.33038{col 29}{space 2} .5057891{col 40}{space 1}    0.75{col 49}{space 3}0.453{col 57}{space 4} .6314846{col 70}{space 3} 2.802779
{txt}{space 12}13  {c |}{col 17}{res}{space 2} .8385709{col 29}{space 2}  .082925{col 40}{space 1}   -1.78{col 49}{space 3}0.075{col 57}{space 4} .6908214{col 70}{space 3}  1.01792
{txt}{space 12}14  {c |}{col 17}{res}{space 2} 1.036489{col 29}{space 2} .2320059{col 40}{space 1}    0.16{col 49}{space 3}0.873{col 57}{space 4} .6683955{col 70}{space 3} 1.607297
{txt}{space 12}15  {c |}{col 17}{res}{space 2} 2.044887{col 29}{space 2} .8413758{col 40}{space 1}    1.74{col 49}{space 3}0.082{col 57}{space 4} .9129345{col 70}{space 3} 4.580355
{txt}{space 12}16  {c |}{col 17}{res}{space 2} 1.478252{col 29}{space 2} .4888277{col 40}{space 1}    1.18{col 49}{space 3}0.237{col 57}{space 4} .7731676{col 70}{space 3} 2.826334
{txt}{space 12}17  {c |}{col 17}{res}{space 2} .6689198{col 29}{space 2} .1070136{col 40}{space 1}   -2.51{col 49}{space 3}0.012{col 57}{space 4} .4888764{col 70}{space 3} .9152696
{txt}{space 12}18  {c |}{col 17}{res}{space 2} .6180259{col 29}{space 2} .1606626{col 40}{space 1}   -1.85{col 49}{space 3}0.064{col 57}{space 4} .3713023{col 70}{space 3} 1.028693
{txt}{space 12}19  {c |}{col 17}{res}{space 2} .5417186{col 29}{space 2} .0580422{col 40}{space 1}   -5.72{col 49}{space 3}0.000{col 57}{space 4} .4391087{col 70}{space 3}  .668306
{txt}{space 12}20  {c |}{col 17}{res}{space 2} .9705662{col 29}{space 2} .0949099{col 40}{space 1}   -0.31{col 49}{space 3}0.760{col 57}{space 4} .8012863{col 70}{space 3} 1.175608
{txt}{space 15} {c |}
{space 8}presrev {c |}
{space 13}2  {c |}{col 17}{res}{space 2}  1.60502{col 29}{space 2} .3205356{col 40}{space 1}    2.37{col 49}{space 3}0.018{col 57}{space 4} 1.085147{col 70}{space 3} 2.373954
{txt}{space 13}3  {c |}{col 17}{res}{space 2} 1.609766{col 29}{space 2} .5058687{col 40}{space 1}    1.52{col 49}{space 3}0.130{col 57}{space 4} .8695061{col 70}{space 3}  2.98025
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 1.602144{col 29}{space 2} .5067635{col 40}{space 1}    1.49{col 49}{space 3}0.136{col 57}{space 4} .8619132{col 70}{space 3} 2.978101
{txt}{space 13}5  {c |}{col 17}{res}{space 2} 1.330219{col 29}{space 2} .5315238{col 40}{space 1}    0.71{col 49}{space 3}0.475{col 57}{space 4} .6078594{col 70}{space 3} 2.911005
{txt}{space 13}6  {c |}{col 17}{res}{space 2} 1.304556{col 29}{space 2} .5527358{col 40}{space 1}    0.63{col 49}{space 3}0.530{col 57}{space 4} .5686063{col 70}{space 3} 2.993049
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. 
. 
. * DESCRIPTIVE STATISTICS FOR EACH PARTISAN CONTROL REGIME [NOTE: THESE VARY ACROSS SUBSAMPLES OF INTEREST] *
. sum wSenComm_chair_pres1 if e(sample) & sendivide==0, detail

                    {txt}wSenComm_chair_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}-.7163319      -.7163319
{txt} 5%    {res}-.5493055      -.7163319
{txt}10%    {res}-.5251514      -.7163319       {txt}Obs         {res}      4,475
{txt}25%    {res}-.4552139      -.7163319       {txt}Sum of wgt. {res}      4,475

{txt}50%    {res}-.3661785                      {txt}Mean          {res}-.3145722
                        {txt}Largest       Std. dev.     {res} .2565557
{txt}75%    {res}-.2196792       .6940686
{txt}90%    {res}-.0447927       .6940686       {txt}Variance      {res} .0658208
{txt}95%    {res}  .208236       .6940686       {txt}Skewness      {res} 1.887141
{txt}99%    {res} .6122074       .6940686       {txt}Kurtosis      {res} 7.304456
{txt}
{com}. sum wSenComm_chair_pres1 if e(sample) & sendivide==1, detail

                    {txt}wSenComm_chair_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}-.2693319      -.7163319
{txt} 5%    {res}-.0833319       -.411764
{txt}10%    {res} .0763208      -.3632139       {txt}Obs         {res}      3,923
{txt}25%    {res} .2632073      -.3632139       {txt}Sum of wgt. {res}      3,923

{txt}50%    {res} .3612073                      {txt}Mean          {res} .3567821
                        {txt}Largest       Std. dev.     {res} .2106762
{txt}75%    {res} .4938942       .7534087
{txt}90%    {res} .6122074       .7534087       {txt}Variance      {res} .0443844
{txt}95%    {res} .6940686       .7534087       {txt}Skewness      {res}-.7035733
{txt}99%    {res} .7534087       .8284615       {txt}Kurtosis      {res} 3.791322
{txt}
{com}. 
. 
. 
. ** CONDITIONAL COEFFICIENT ANALYSIS TESTS: DIRECTION [+] ** 
. 
. * DIFFERENCE BETWEEN DIVIDED AND UNIFIED PARTISAN CONTROL OF SENATE & PRESIDENCY: INTERQUARTILE UNIT CHANGE IN "wSenComm_chair_pres1"  *
. lincomest (chair_pres1 * 0.2355347 +  1.sendivide#c.chair_pres1 * 0.2306869) - chair_pres1 * 0.2355347, eform(hr)
{txt}Confidence interval for formula:
{res}(chair_pres1*0.2355347+1.sendivide#c.chair_pres1*0.2306869)-chair_pres1*0.2355347

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} 1.275035{col 26}{space 2} .1276124{col 37}{space 1}    2.43{col 46}{space 3}0.015{col 54}{space 4} 1.047923{col 67}{space 3} 1.551369
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix model2a = r(table)
{txt}
{com}. mat list model2a
{res}
{txt}model2a[9,1]
               (1)
     b {res} 1.2750354
{txt}    se {res} .12761235
{txt}     z {res} 2.4276674
{txt}pvalue {res} .01519627
{txt}    ll {res} 1.0479232
{txt}    ul {res} 1.5513687
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         1
{reset}
{com}. 
. *
. *
. *
. *
. 
. 
. 
. *** MODEL G.2B: FULL SAMPLE: |COMMITTEE CHAIR - PRESIDENT| & PRIORCONFIRM==1 [CCOX SEMIPARAMETRIC MODEL] ***
. 
. stcox  c.chair_pres1##i.sendivide  pressenfloorabsdist   chair_experience_1  committeestaffsize ln_combills_workload   pres_app_m first90 preselection lameduck   kv_workload  polarization   workload  female priorconfirm denied  x_itier_2 x_itier_3 x_itier_4 defense infrastructure social fvra firstrecess secondrecess policy_majagency  i.kbcom_1  i.presrev  if priorconfirm==1,  vce(cluster kbcom_1)

{col 9}{txt}Failure {bf:_d}: {res}confirmbinary
{col 3}{txt}Analysis time {bf:_t}: {res}legvetdur2plus1

{txt}note: {bf:priorconfirm} omitted because of collinearity.
Iteration 0:  Log pseudolikelihood = {res}  -6710.12
{txt}Iteration 1:  Log pseudolikelihood = {res}-6604.4034
{txt}Iteration 2:  Log pseudolikelihood = {res}-6572.4444
{txt}Iteration 3:  Log pseudolikelihood = {res} -6569.939
{txt}Iteration 4:  Log pseudolikelihood = {res}-6569.8614
{txt}Iteration 5:  Log pseudolikelihood = {res}-6569.8485
{txt}Iteration 6:  Log pseudolikelihood = {res}-6569.8438
{txt}Iteration 7:  Log pseudolikelihood = {res}-6569.8421
{txt}Iteration 8:  Log pseudolikelihood = {res}-6569.8414
{txt}Iteration 9:  Log pseudolikelihood = {res}-6569.8412
{txt}Iteration 10: Log pseudolikelihood = {res}-6569.8411
{txt}Iteration 11: Log pseudolikelihood = {res}-6569.8411
{txt}Iteration 12: Log pseudolikelihood = {res}-6569.8411
{txt}Iteration 13: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 14: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 15: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 16: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 17: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 18: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 19: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 20: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 21: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 22: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 23: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 24: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 25: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 26: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 27: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 28: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 29: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 30: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 31: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 32: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 33: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 34: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 35: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 36: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 37: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 38: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 39: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 40: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 41: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 42: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 43: Log pseudolikelihood = {res} -6569.841
{txt}Iteration 44: Log pseudolikelihood = {res} -6569.841
{txt}Refining estimates:
Iteration 0:  Log pseudolikelihood = {res} -6569.841

{txt}Cox regression with Breslow method for ties

No. of subjects = {res}{ralign 7:1,481}{col 54}{txt}{lalign 13:Number of obs} = {res}{ralign 9:1,481}
{txt}No. of failures = {res}{ralign 7:1,022}
{txt}Time at risk    = {res}{ralign 7:159,446}
{col 54}{txt}{lalign 13:Wald chi2({res:18})} = {res}{ralign 9:141503.75}
{txt}Log pseudolikelihood = {res}-6569.841{col 54}{txt}{lalign 13:Prob > chi2} = {res}{ralign 9:0.0000}

{txt}{ralign 81:(Std. err. adjusted for {res:20} clusters in {res:kbcom_1})}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}             _t{col 17}{c |} Haz. ratio{col 29}   std. err.{col 41}      z{col 49}   P>|z|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}chair_pres1 {c |}{col 17}{res}{space 2} .7250878{col 29}{space 2} .3256596{col 40}{space 1}   -0.72{col 49}{space 3}0.474{col 57}{space 4} .3006695{col 70}{space 3} 1.748605
{txt}{space 4}1.sendivide {c |}{col 17}{res}{space 2} .5364684{col 29}{space 2} .2195411{col 40}{space 1}   -1.52{col 49}{space 3}0.128{col 57}{space 4}  .240549{col 70}{space 3} 1.196423
{txt}{space 15} {c |}
{space 6}sendivide#{c |}
{space 2}c.chair_pres1 {c |}
{space 13}1  {c |}{col 17}{res}{space 2} 1.604512{col 29}{space 2} .6058343{col 40}{space 1}    1.25{col 49}{space 3}0.210{col 57}{space 4} .7654991{col 70}{space 3}  3.36311
{txt}{space 15} {c |}
pressenfloora~t {c |}{col 17}{res}{space 2}  .805045{col 29}{space 2} .7410573{col 40}{space 1}   -0.24{col 49}{space 3}0.814{col 57}{space 4}  .132518{col 70}{space 3} 4.890636
{txt}chair_experie~1 {c |}{col 17}{res}{space 2} 1.013111{col 29}{space 2} .0042068{col 40}{space 1}    3.14{col 49}{space 3}0.002{col 57}{space 4}   1.0049{col 70}{space 3}  1.02139
{txt}committeestaf~e {c |}{col 17}{res}{space 2} .9898096{col 29}{space 2} .0047399{col 40}{space 1}   -2.14{col 49}{space 3}0.032{col 57}{space 4} .9805631{col 70}{space 3} .9991432
{txt}ln_combills_w~d {c |}{col 17}{res}{space 2} 1.067635{col 29}{space 2} .1900415{col 40}{space 1}    0.37{col 49}{space 3}0.713{col 57}{space 4} .7531946{col 70}{space 3} 1.513348
{txt}{space 5}pres_app_m {c |}{col 17}{res}{space 2} .9975244{col 29}{space 2} .0057287{col 40}{space 1}   -0.43{col 49}{space 3}0.666{col 57}{space 4} .9863592{col 70}{space 3} 1.008816
{txt}{space 8}first90 {c |}{col 17}{res}{space 2} 1.800659{col 29}{space 2} .3330224{col 40}{space 1}    3.18{col 49}{space 3}0.001{col 57}{space 4} 1.253159{col 70}{space 3} 2.587359
{txt}{space 3}preselection {c |}{col 17}{res}{space 2}  .603341{col 29}{space 2} .0635512{col 40}{space 1}   -4.80{col 49}{space 3}0.000{col 57}{space 4} .4907993{col 70}{space 3} .7416889
{txt}{space 7}lameduck {c |}{col 17}{res}{space 2} 1.108673{col 29}{space 2} .1004963{col 40}{space 1}    1.14{col 49}{space 3}0.255{col 57}{space 4}  .928209{col 70}{space 3} 1.324223
{txt}{space 4}kv_workload {c |}{col 17}{res}{space 2} 1.000001{col 29}{space 2}   .00005{col 40}{space 1}    0.03{col 49}{space 3}0.977{col 57}{space 4} .9999035{col 70}{space 3} 1.000099
{txt}{space 3}polarization {c |}{col 17}{res}{space 2} .0112478{col 29}{space 2} .0230096{col 40}{space 1}   -2.19{col 49}{space 3}0.028{col 57}{space 4} .0002041{col 70}{space 3}  .619979
{txt}{space 7}workload {c |}{col 17}{res}{space 2} 1.001967{col 29}{space 2} .0015179{col 40}{space 1}    1.30{col 49}{space 3}0.195{col 57}{space 4}  .998996{col 70}{space 3} 1.004946
{txt}{space 9}female {c |}{col 17}{res}{space 2} 1.044626{col 29}{space 2} .0853062{col 40}{space 1}    0.53{col 49}{space 3}0.593{col 57}{space 4} .8901231{col 70}{space 3} 1.225947
{txt}{space 3}priorconfirm {c |}{col 17}{res}{space 2}        1{col 29}{txt}  (omitted)
{space 9}denied {c |}{col 17}{res}{space 2} .5914272{col 29}{space 2} .0923623{col 40}{space 1}   -3.36{col 49}{space 3}0.001{col 57}{space 4} .4354822{col 70}{space 3} .8032157
{txt}{space 6}x_itier_2 {c |}{col 17}{res}{space 2} .8504201{col 29}{space 2}   .08783{col 40}{space 1}   -1.57{col 49}{space 3}0.117{col 57}{space 4} .6945809{col 70}{space 3} 1.041224
{txt}{space 6}x_itier_3 {c |}{col 17}{res}{space 2} .6593878{col 29}{space 2} .1266785{col 40}{space 1}   -2.17{col 49}{space 3}0.030{col 57}{space 4} .4524931{col 70}{space 3} .9608815
{txt}{space 6}x_itier_4 {c |}{col 17}{res}{space 2} .6669474{col 29}{space 2} .0636822{col 40}{space 1}   -4.24{col 49}{space 3}0.000{col 57}{space 4}  .553116{col 70}{space 3} .8042055
{txt}{space 8}defense {c |}{col 17}{res}{space 2} 1.025718{col 29}{space 2} .1482616{col 40}{space 1}    0.18{col 49}{space 3}0.861{col 57}{space 4} .7726656{col 70}{space 3} 1.361646
{txt}{space 1}infrastructure {c |}{col 17}{res}{space 2} .8652658{col 29}{space 2} .1342446{col 40}{space 1}   -0.93{col 49}{space 3}0.351{col 57}{space 4} .6383914{col 70}{space 3} 1.172768
{txt}{space 9}social {c |}{col 17}{res}{space 2} .9263398{col 29}{space 2} .1501674{col 40}{space 1}   -0.47{col 49}{space 3}0.637{col 57}{space 4} .6741917{col 70}{space 3} 1.272791
{txt}{space 11}fvra {c |}{col 17}{res}{space 2} 1.094502{col 29}{space 2} .1442178{col 40}{space 1}    0.69{col 49}{space 3}0.493{col 57}{space 4} .8453909{col 70}{space 3} 1.417019
{txt}{space 4}firstrecess {c |}{col 17}{res}{space 2} .9588033{col 29}{space 2} .1018215{col 40}{space 1}   -0.40{col 49}{space 3}0.692{col 57}{space 4} .7786369{col 70}{space 3} 1.180658
{txt}{space 3}secondrecess {c |}{col 17}{res}{space 2} .7931231{col 29}{space 2} .1021431{col 40}{space 1}   -1.80{col 49}{space 3}0.072{col 57}{space 4} .6161945{col 70}{space 3} 1.020853
{txt}policy_majage~y {c |}{col 17}{res}{space 2} 1.107697{col 29}{space 2}  .106975{col 40}{space 1}    1.06{col 49}{space 3}0.290{col 57}{space 4} .9166779{col 70}{space 3} 1.338521
{txt}{space 15} {c |}
{space 8}kbcom_1 {c |}
{space 13}2  {c |}{col 17}{res}{space 2} .5688192{col 29}{space 2} .0844249{col 40}{space 1}   -3.80{col 49}{space 3}0.000{col 57}{space 4} .4252437{col 70}{space 3} .7608704
{txt}{space 13}3  {c |}{col 17}{res}{space 2} .5455551{col 29}{space 2} .0317046{col 40}{space 1}  -10.43{col 49}{space 3}0.000{col 57}{space 4} .4868235{col 70}{space 3} .6113721
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 2.082036{col 29}{space 2} .5886191{col 40}{space 1}    2.59{col 49}{space 3}0.009{col 57}{space 4} 1.196306{col 70}{space 3} 3.623549
{txt}{space 13}5  {c |}{col 17}{res}{space 2} .7523367{col 29}{space 2} .1560808{col 40}{space 1}   -1.37{col 49}{space 3}0.170{col 57}{space 4} .5009804{col 70}{space 3} 1.129806
{txt}{space 13}6  {c |}{col 17}{res}{space 2} 1.017387{col 29}{space 2} .1997972{col 40}{space 1}    0.09{col 49}{space 3}0.930{col 57}{space 4} .6923488{col 70}{space 3} 1.495021
{txt}{space 13}7  {c |}{col 17}{res}{space 2} .6816819{col 29}{space 2} .1007645{col 40}{space 1}   -2.59{col 49}{space 3}0.010{col 57}{space 4} .5102221{col 70}{space 3} .9107607
{txt}{space 13}8  {c |}{col 17}{res}{space 2} .6529341{col 29}{space 2} .2498794{col 40}{space 1}   -1.11{col 49}{space 3}0.265{col 57}{space 4} .3083987{col 70}{space 3} 1.382376
{txt}{space 13}9  {c |}{col 17}{res}{space 2}  .484906{col 29}{space 2} .0618316{col 40}{space 1}   -5.68{col 49}{space 3}0.000{col 57}{space 4} .3776753{col 70}{space 3} .6225818
{txt}{space 12}10  {c |}{col 17}{res}{space 2} .6949936{col 29}{space 2} .1524847{col 40}{space 1}   -1.66{col 49}{space 3}0.097{col 57}{space 4} .4520884{col 70}{space 3} 1.068411
{txt}{space 12}11  {c |}{col 17}{res}{space 2} .7269797{col 29}{space 2}  .261207{col 40}{space 1}   -0.89{col 49}{space 3}0.375{col 57}{space 4} .3594858{col 70}{space 3} 1.470154
{txt}{space 12}12  {c |}{col 17}{res}{space 2} .7614711{col 29}{space 2} .2022186{col 40}{space 1}   -1.03{col 49}{space 3}0.305{col 57}{space 4} .4524866{col 70}{space 3} 1.281448
{txt}{space 12}13  {c |}{col 17}{res}{space 2} .3346558{col 29}{space 2} .0552643{col 40}{space 1}   -6.63{col 49}{space 3}0.000{col 57}{space 4} .2421212{col 70}{space 3} .4625556
{txt}{space 12}14  {c |}{col 17}{res}{space 2} .6179794{col 29}{space 2} .2843208{col 40}{space 1}   -1.05{col 49}{space 3}0.296{col 57}{space 4} .2508141{col 70}{space 3} 1.522636
{txt}{space 12}15  {c |}{col 17}{res}{space 2} .7078483{col 29}{space 2} .2599191{col 40}{space 1}   -0.94{col 49}{space 3}0.347{col 57}{space 4} .3446533{col 70}{space 3} 1.453778
{txt}{space 12}16  {c |}{col 17}{res}{space 2} .6775282{col 29}{space 2} .2011982{col 40}{space 1}   -1.31{col 49}{space 3}0.190{col 57}{space 4} .3785779{col 70}{space 3} 1.212549
{txt}{space 12}17  {c |}{col 17}{res}{space 2} .5415031{col 29}{space 2} .0598146{col 40}{space 1}   -5.55{col 49}{space 3}0.000{col 57}{space 4} .4360908{col 70}{space 3} .6723958
{txt}{space 12}18  {c |}{col 17}{res}{space 2} 1.901258{col 29}{space 2} .8027546{col 40}{space 1}    1.52{col 49}{space 3}0.128{col 57}{space 4} .8310832{col 70}{space 3} 4.349485
{txt}{space 12}19  {c |}{col 17}{res}{space 2} 6.19e-20{col 29}{space 2}        .{col 40}{space 1}       .{col 49}{space 3}    .{col 57}{space 4}        .{col 70}{space 3}        .
{txt}{space 12}20  {c |}{col 17}{res}{space 2} .4898958{col 29}{space 2} .0980796{col 40}{space 1}   -3.56{col 49}{space 3}0.000{col 57}{space 4}  .330894{col 70}{space 3} .7253014
{txt}{space 15} {c |}
{space 8}presrev {c |}
{space 13}2  {c |}{col 17}{res}{space 2}  2.00442{col 29}{space 2} .5541464{col 40}{space 1}    2.52{col 49}{space 3}0.012{col 57}{space 4} 1.165906{col 70}{space 3} 3.445988
{txt}{space 13}3  {c |}{col 17}{res}{space 2} 1.756298{col 29}{space 2} .6408273{col 40}{space 1}    1.54{col 49}{space 3}0.123{col 57}{space 4} .8590475{col 70}{space 3} 3.590703
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 1.260308{col 29}{space 2} .7320369{col 40}{space 1}    0.40{col 49}{space 3}0.690{col 57}{space 4}  .403706{col 70}{space 3} 3.934489
{txt}{space 13}5  {c |}{col 17}{res}{space 2} 1.050322{col 29}{space 2}  .447781{col 40}{space 1}    0.12{col 49}{space 3}0.908{col 57}{space 4} .4554411{col 70}{space 3} 2.422216
{txt}{space 13}6  {c |}{col 17}{res}{space 2}  1.64904{col 29}{space 2} .9342538{col 40}{space 1}    0.88{col 49}{space 3}0.377{col 57}{space 4} .5432353{col 70}{space 3}  5.00581
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. 
. * DESCRIPTIVE STATISTICS FOR EACH PARTISAN CONTROL REGIME [NOTE: THESE VARY ACROSS SUBSAMPLES OF INTEREST] *
. sum wSenComm_chair_pres1 if e(sample) & sendivide==0, detail

                    {txt}wSenComm_chair_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}-.7163319      -.7163319
{txt} 5%    {res}-.5463055      -.7163319
{txt}10%    {res}-.5065913      -.7163319       {txt}Obs         {res}        713
{txt}25%    {res}-.4493055      -.7163319       {txt}Sum of wgt. {res}        713

{txt}50%    {res}-.3046792                      {txt}Mean          {res}-.2873832
                        {txt}Largest       Std. dev.     {res} .2103798
{txt}75%    {res}-.1762139       .4892833
{txt}90%    {res}-.0447927       .5914087       {txt}Variance      {res} .0442597
{txt}95%    {res} .1377861       .5914087       {txt}Skewness      {res} 1.295271
{txt}99%    {res} .4892833       .6940686       {txt}Kurtosis      {res} 6.086439
{txt}
{com}. sum wSenComm_chair_pres1 if e(sample) & sendivide==1, detail

                    {txt}wSenComm_chair_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}-.2693319      -.4493055
{txt} 5%    {res}-.0833319      -.3517167
{txt}10%    {res} .0100685      -.2693319       {txt}Obs         {res}        768
{txt}25%    {res} .1968486      -.2693319       {txt}Sum of wgt. {res}        768

{txt}50%    {res} .3327861                      {txt}Mean          {res} .3084411
                        {txt}Largest       Std. dev.     {res} .2332723
{txt}75%    {res} .4782646       .7534087
{txt}90%    {res} .5828941       .7534087       {txt}Variance      {res} .0544159
{txt}95%    {res} .6940686       .7534087       {txt}Skewness      {res} -.536575
{txt}99%    {res} .6973208       .7534087       {txt}Kurtosis      {res} 3.100178
{txt}
{com}. 
. 
. ** CONDITIONAL COEFFICIENT ANALYSIS TESTS: DIRECTION [+] ** 
. 
. * DIFFERENCE BETWEEN DIVIDED AND UNIFIED PARTISAN CONTROL OF SENATE & PRESIDENCY: INTERQUARTILE UNIT CHANGE IN "wSenComm_chair_pres1"  *
. lincomest (chair_pres1 * 0.2730916 +  1.sendivide#c.chair_pres1 * 0.281416) - chair_pres1 * 0.2730916, eform(hr)
{txt}Confidence interval for formula:
{res}(chair_pres1*0.2730916+1.sendivide#c.chair_pres1*0.281416)-chair_pres1*0.2730916

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} 1.142317{col 26}{space 2} .1213798{col 37}{space 1}    1.25{col 46}{space 3}0.210{col 54}{space 4} .9275561{col 67}{space 3} 1.406803
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix model2b = r(table)
{txt}
{com}. mat list model2b
{res}
{txt}model2b[9,1]
               (1)
     b {res} 1.1423173
{txt}    se {res} .12137984
{txt}     z {res} 1.2522306
{txt}pvalue {res} .21048587
{txt}    ll {res} .92755608
{txt}    ul {res} 1.4068032
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         1
{reset}
{com}. 
. 
. 
. 
. *****************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. 
. 
. 
. 
. *** MODEL H.3A: FULL SAMPLE: |COMMITTEE MEDIAN - PRESIDENT| & PRIORCONFIRM==0 [WEIBULL PARAMETRIC MODEL] ***
. 
. streg  c.committee_pres1##i.sendivide    pressenfloorabsdist   experience_median  committeestaffsize ln_combills_workload   pres_app_m first90 preselection lameduck   kv_workload  polarization   workload  female priorconfirm denied  x_itier_2 x_itier_3 x_itier_4 defense infrastructure social fvra firstrecess secondrecess policy_majagency   i.kbcom_1  i.presrev if priorconfirm==0,  distribution(weibull) vce(cluster kbcom_1)

{col 9}{txt}Failure {bf:_d}: {res}confirmbinary
{col 3}{txt}Analysis time {bf:_t}: {res}legvetdur2plus1
{txt}note: {bf:priorconfirm} omitted because of collinearity.

Fitting constant-only model:
Iteration 0:  Log pseudolikelihood = {res}  -11911.4
{txt}Iteration 1:  Log pseudolikelihood = {res}-11899.845
{txt}Iteration 2:  Log pseudolikelihood = {res}-11899.844

{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-11899.844}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-11839.211}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-10998.661}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-10974.829}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-10974.703}  
Iteration 5:{space 2}Log pseudolikelihood = {res:-10974.702}  
{res}
{txt}Weibull PH regression

No. of subjects = {res}{ralign 7:8,398}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:8,398}
{txt}No. of failures = {res}{ralign 7:6,054}
{txt}Time at risk    = {res}{ralign 7:828,365}
{col 57}{txt}{lalign 13:{help j_robustsingular##|_new:Wald chi2(17)}} = {res}{ralign 6:.}
{txt}Log pseudolikelihood = {res}-10974.702{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:.}

{txt}{ralign 81:(Std. err. adjusted for {res:20} clusters in {res:kbcom_1})}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}             _t{col 17}{c |} Haz. ratio{col 29}   std. err.{col 41}      z{col 49}   P>|z|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
committee_pres1 {c |}{col 17}{res}{space 2} .4035076{col 29}{space 2} .3039363{col 40}{space 1}   -1.20{col 49}{space 3}0.228{col 57}{space 4} .0921927{col 70}{space 3} 1.766066
{txt}{space 4}1.sendivide {c |}{col 17}{res}{space 2} .2608154{col 29}{space 2} .1655564{col 40}{space 1}   -2.12{col 49}{space 3}0.034{col 57}{space 4} .0751658{col 70}{space 3} .9049944
{txt}{space 15} {c |}
{space 6}sendivide#{c |}
{space 13}c. {c |}
committee_pres1 {c |}
{space 13}1  {c |}{col 17}{res}{space 2} 5.943771{col 29}{space 2} 4.635628{col 40}{space 1}    2.29{col 49}{space 3}0.022{col 57}{space 4} 1.288838{col 70}{space 3} 27.41105
{txt}{space 15} {c |}
pressenfloora~t {c |}{col 17}{res}{space 2} .7912933{col 29}{space 2} .7291153{col 40}{space 1}   -0.25{col 49}{space 3}0.799{col 57}{space 4} .1300234{col 70}{space 3} 4.815635
{txt}experience_me~n {c |}{col 17}{res}{space 2} .9975637{col 29}{space 2}  .013986{col 40}{space 1}   -0.17{col 49}{space 3}0.862{col 57}{space 4} .9705249{col 70}{space 3} 1.025356
{txt}committeestaf~e {c |}{col 17}{res}{space 2}  .991882{col 29}{space 2} .0051072{col 40}{space 1}   -1.58{col 49}{space 3}0.113{col 57}{space 4} .9819224{col 70}{space 3} 1.001943
{txt}ln_combills_w~d {c |}{col 17}{res}{space 2} .8227913{col 29}{space 2} .0911031{col 40}{space 1}   -1.76{col 49}{space 3}0.078{col 57}{space 4} .6622788{col 70}{space 3} 1.022206
{txt}{space 5}pres_app_m {c |}{col 17}{res}{space 2} 1.004437{col 29}{space 2}   .00291{col 40}{space 1}    1.53{col 49}{space 3}0.127{col 57}{space 4} .9987494{col 70}{space 3} 1.010156
{txt}{space 8}first90 {c |}{col 17}{res}{space 2} 2.607555{col 29}{space 2}  .238031{col 40}{space 1}   10.50{col 49}{space 3}0.000{col 57}{space 4} 2.180376{col 70}{space 3} 3.118426
{txt}{space 3}preselection {c |}{col 17}{res}{space 2} .8305663{col 29}{space 2} .0585652{col 40}{space 1}   -2.63{col 49}{space 3}0.008{col 57}{space 4} .7233594{col 70}{space 3} .9536621
{txt}{space 7}lameduck {c |}{col 17}{res}{space 2} .8371448{col 29}{space 2} .0675855{col 40}{space 1}   -2.20{col 49}{space 3}0.028{col 57}{space 4} .7146284{col 70}{space 3} .9806656
{txt}{space 4}kv_workload {c |}{col 17}{res}{space 2} .9999626{col 29}{space 2} .0000361{col 40}{space 1}   -1.04{col 49}{space 3}0.300{col 57}{space 4}  .999892{col 70}{space 3} 1.000033
{txt}{space 3}polarization {c |}{col 17}{res}{space 2} .0276711{col 29}{space 2} .0426516{col 40}{space 1}   -2.33{col 49}{space 3}0.020{col 57}{space 4}  .001349{col 70}{space 3} .5676081
{txt}{space 7}workload {c |}{col 17}{res}{space 2}  1.00237{col 29}{space 2} .0016616{col 40}{space 1}    1.43{col 49}{space 3}0.153{col 57}{space 4} .9991191{col 70}{space 3} 1.005632
{txt}{space 9}female {c |}{col 17}{res}{space 2} .9881623{col 29}{space 2} .0463199{col 40}{space 1}   -0.25{col 49}{space 3}0.799{col 57}{space 4} .9014225{col 70}{space 3} 1.083249
{txt}{space 3}priorconfirm {c |}{col 17}{res}{space 2}        1{col 29}{txt}  (omitted)
{space 9}denied {c |}{col 17}{res}{space 2} .6121408{col 29}{space 2} .0633303{col 40}{space 1}   -4.74{col 49}{space 3}0.000{col 57}{space 4} .4997911{col 70}{space 3} .7497459
{txt}{space 6}x_itier_2 {c |}{col 17}{res}{space 2} .9527482{col 29}{space 2} .0536812{col 40}{space 1}   -0.86{col 49}{space 3}0.390{col 57}{space 4} .8531363{col 70}{space 3} 1.063991
{txt}{space 6}x_itier_3 {c |}{col 17}{res}{space 2}  .778898{col 29}{space 2} .1840815{col 40}{space 1}   -1.06{col 49}{space 3}0.290{col 57}{space 4} .4901299{col 70}{space 3} 1.237799
{txt}{space 6}x_itier_4 {c |}{col 17}{res}{space 2} .7866393{col 29}{space 2} .1120743{col 40}{space 1}   -1.68{col 49}{space 3}0.092{col 57}{space 4} .5949809{col 70}{space 3} 1.040036
{txt}{space 8}defense {c |}{col 17}{res}{space 2} .9574858{col 29}{space 2} .0925202{col 40}{space 1}   -0.45{col 49}{space 3}0.653{col 57}{space 4} .7922864{col 70}{space 3} 1.157131
{txt}{space 1}infrastructure {c |}{col 17}{res}{space 2} .9548154{col 29}{space 2} .1073087{col 40}{space 1}   -0.41{col 49}{space 3}0.681{col 57}{space 4} .7660473{col 70}{space 3} 1.190099
{txt}{space 9}social {c |}{col 17}{res}{space 2} .9000754{col 29}{space 2} .0907045{col 40}{space 1}   -1.04{col 49}{space 3}0.296{col 57}{space 4} .7387536{col 70}{space 3} 1.096625
{txt}{space 11}fvra {c |}{col 17}{res}{space 2} 1.234525{col 29}{space 2} .0916109{col 40}{space 1}    2.84{col 49}{space 3}0.005{col 57}{space 4} 1.067417{col 70}{space 3} 1.427793
{txt}{space 4}firstrecess {c |}{col 17}{res}{space 2} 1.037506{col 29}{space 2} .0587561{col 40}{space 1}    0.65{col 49}{space 3}0.516{col 57}{space 4} .9285073{col 70}{space 3}   1.1593
{txt}{space 3}secondrecess {c |}{col 17}{res}{space 2} .7926026{col 29}{space 2} .0771048{col 40}{space 1}   -2.39{col 49}{space 3}0.017{col 57}{space 4} .6550133{col 70}{space 3} .9590932
{txt}policy_majage~y {c |}{col 17}{res}{space 2} 1.336242{col 29}{space 2} .1095702{col 40}{space 1}    3.53{col 49}{space 3}0.000{col 57}{space 4} 1.137857{col 70}{space 3} 1.569215
{txt}{space 15} {c |}
{space 8}kbcom_1 {c |}
{space 13}2  {c |}{col 17}{res}{space 2}  1.09177{col 29}{space 2} .1741042{col 40}{space 1}    0.55{col 49}{space 3}0.582{col 57}{space 4}  .798712{col 70}{space 3} 1.492354
{txt}{space 13}3  {c |}{col 17}{res}{space 2} 1.022681{col 29}{space 2} .0964183{col 40}{space 1}    0.24{col 49}{space 3}0.812{col 57}{space 4} .8501375{col 70}{space 3} 1.230245
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 2.888514{col 29}{space 2} .3795757{col 40}{space 1}    8.07{col 49}{space 3}0.000{col 57}{space 4} 2.232642{col 70}{space 3} 3.737057
{txt}{space 13}5  {c |}{col 17}{res}{space 2} 1.473857{col 29}{space 2} .3221937{col 40}{space 1}    1.77{col 49}{space 3}0.076{col 57}{space 4} .9602352{col 70}{space 3}  2.26221
{txt}{space 13}6  {c |}{col 17}{res}{space 2} 1.781658{col 29}{space 2} .3468943{col 40}{space 1}    2.97{col 49}{space 3}0.003{col 57}{space 4} 1.216446{col 70}{space 3} 2.609492
{txt}{space 13}7  {c |}{col 17}{res}{space 2} 1.246782{col 29}{space 2} .1505439{col 40}{space 1}    1.83{col 49}{space 3}0.068{col 57}{space 4} .9840373{col 70}{space 3} 1.579682
{txt}{space 13}8  {c |}{col 17}{res}{space 2} 1.097651{col 29}{space 2} .3963958{col 40}{space 1}    0.26{col 49}{space 3}0.796{col 57}{space 4} .5408403{col 70}{space 3} 2.227715
{txt}{space 13}9  {c |}{col 17}{res}{space 2} 1.067292{col 29}{space 2} .1855749{col 40}{space 1}    0.37{col 49}{space 3}0.708{col 57}{space 4} .7590687{col 70}{space 3} 1.500671
{txt}{space 12}10  {c |}{col 17}{res}{space 2} .7846214{col 29}{space 2} .2358562{col 40}{space 1}   -0.81{col 49}{space 3}0.420{col 57}{space 4} .4353014{col 70}{space 3} 1.414263
{txt}{space 12}11  {c |}{col 17}{res}{space 2} 1.314216{col 29}{space 2}  .394976{col 40}{space 1}    0.91{col 49}{space 3}0.363{col 57}{space 4} .7291984{col 70}{space 3} 2.368579
{txt}{space 12}12  {c |}{col 17}{res}{space 2} 1.307195{col 29}{space 2} .5820999{col 40}{space 1}    0.60{col 49}{space 3}0.547{col 57}{space 4} .5461304{col 70}{space 3} 3.128847
{txt}{space 12}13  {c |}{col 17}{res}{space 2} .7308314{col 29}{space 2} .0927797{col 40}{space 1}   -2.47{col 49}{space 3}0.014{col 57}{space 4} .5698446{col 70}{space 3} .9372985
{txt}{space 12}14  {c |}{col 17}{res}{space 2} 1.079548{col 29}{space 2} .2568302{col 40}{space 1}    0.32{col 49}{space 3}0.748{col 57}{space 4} .6772302{col 70}{space 3} 1.720867
{txt}{space 12}15  {c |}{col 17}{res}{space 2} 2.063955{col 29}{space 2} 1.026533{col 40}{space 1}    1.46{col 49}{space 3}0.145{col 57}{space 4} .7786544{col 70}{space 3}  5.47086
{txt}{space 12}16  {c |}{col 17}{res}{space 2} 1.457908{col 29}{space 2} .5659503{col 40}{space 1}    0.97{col 49}{space 3}0.331{col 57}{space 4} .6812387{col 70}{space 3} 3.120046
{txt}{space 12}17  {c |}{col 17}{res}{space 2} .5705727{col 29}{space 2} .1124531{col 40}{space 1}   -2.85{col 49}{space 3}0.004{col 57}{space 4} .3877478{col 70}{space 3} .8396005
{txt}{space 12}18  {c |}{col 17}{res}{space 2} .4517092{col 29}{space 2} .1464526{col 40}{space 1}   -2.45{col 49}{space 3}0.014{col 57}{space 4} .2392673{col 70}{space 3} .8527751
{txt}{space 12}19  {c |}{col 17}{res}{space 2} .5505108{col 29}{space 2} .0743415{col 40}{space 1}   -4.42{col 49}{space 3}0.000{col 57}{space 4} .4224923{col 70}{space 3} .7173199
{txt}{space 12}20  {c |}{col 17}{res}{space 2} .9707417{col 29}{space 2} .1384155{col 40}{space 1}   -0.21{col 49}{space 3}0.835{col 57}{space 4} .7340626{col 70}{space 3} 1.283732
{txt}{space 15} {c |}
{space 8}presrev {c |}
{space 13}2  {c |}{col 17}{res}{space 2} 1.789585{col 29}{space 2} .4095429{col 40}{space 1}    2.54{col 49}{space 3}0.011{col 57}{space 4} 1.142764{col 70}{space 3} 2.802516
{txt}{space 13}3  {c |}{col 17}{res}{space 2} 1.625038{col 29}{space 2} .5443524{col 40}{space 1}    1.45{col 49}{space 3}0.147{col 57}{space 4} .8428098{col 70}{space 3} 3.133268
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 1.696818{col 29}{space 2} .4673613{col 40}{space 1}    1.92{col 49}{space 3}0.055{col 57}{space 4} .9889754{col 70}{space 3} 2.911287
{txt}{space 13}5  {c |}{col 17}{res}{space 2}  1.28575{col 29}{space 2}  .543835{col 40}{space 1}    0.59{col 49}{space 3}0.552{col 57}{space 4} .5612068{col 70}{space 3} 2.945711
{txt}{space 13}6  {c |}{col 17}{res}{space 2} 1.081191{col 29}{space 2} .5513454{col 40}{space 1}    0.15{col 49}{space 3}0.878{col 57}{space 4} .3979592{col 70}{space 3} 2.937422
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} .3273034{col 29}{space 2}  .273274{col 40}{space 1}   -1.34{col 49}{space 3}0.181{col 57}{space 4} .0637177{col 70}{space 3} 1.681282
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}/ln_p {c |}{col 17}{res}{space 2} .0731491{col 29}{space 2} .0214749{col 40}{space 1}    3.41{col 49}{space 3}0.001{col 57}{space 4} .0310591{col 70}{space 3} .1152391
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
              p {c |}{col 17}{res}{space 2} 1.075891{col 29}{space 2} .0231046{col 57}{space 4} 1.031546{col 70}{space 3} 1.122142
{txt}            1/p {c |}{col 17}{res}{space 2} .9294622{col 29}{space 2} .0199601{col 57}{space 4} .8911531{col 70}{space 3} .9694183
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {bf:_cons} estimates baseline hazard{txt}.{p_end}

{com}. *
. 
. * DESCRIPTIVE STATISTICS FOR EACH PARTISAN CONTROL REGIME [NOTE: THESE VARY ACROSS SUBSAMPLES OF INTEREST] *
. sum wSenComm_committee_pres1 if e(sample) & sendivide==0, detail

                  {txt}wSenComm_committee_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}-.5386078      -.5386078
{txt} 5%    {res}-.4976805      -.5386078
{txt}10%    {res} -.412061      -.5386078       {txt}Obs         {res}      4,475
{txt}25%    {res}-.3707183      -.5386078       {txt}Sum of wgt. {res}      4,475

{txt}50%    {res}-.2758437                      {txt}Mean          {res}-.1949483
                        {txt}Largest       Std. dev.     {res} .2310165
{txt}75%    {res}-.0624062        .490939
{txt}90%    {res} .1603195        .490939       {txt}Variance      {res} .0533686
{txt}95%    {res} .2121217        .490939       {txt}Skewness      {res} .8403455
{txt}99%    {res} .4655938        .490939       {txt}Kurtosis      {res} 2.951248
{txt}
{com}. sum wSenComm_committee_pres1 if e(sample) & sendivide==1, detail

                  {txt}wSenComm_committee_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}-.1966079      -.5386078
{txt} 5%    {res} -.115061      -.2201461
{txt}10%    {res}-.0252148      -.1966079       {txt}Obs         {res}      3,923
{txt}25%    {res} .0905807      -.1966079       {txt}Sum of wgt. {res}      3,923

{txt}50%    {res} .2273195                      {txt}Mean          {res} .2177173
                        {txt}Largest       Std. dev.     {res} .1758748
{txt}75%    {res} .3489552        .490939
{txt}90%    {res} .4655938        .490939       {txt}Variance      {res}  .030932
{txt}95%    {res}  .490939        .490939       {txt}Skewness      {res}-.4540304
{txt}99%    {res}  .490939        .676923       {txt}Kurtosis      {res} 2.835072
{txt}
{com}. 
. 
. 
. ** CONDITIONAL COEFFICIENT ANALYSIS TESTS: DIRECTION [+] ** 
. 
. * DIFFERENCE BETWEEN DIVIDED AND UNIFIED PARTISAN CONTROL OF SENATE & PRESIDENCY: INTERQUARTILE UNIT CHANGE IN "wSenComm_committee_pres1"  *
. lincomest (committee_pres1 * 0.3083121 +  1.sendivide#c.committee_pres1 * 0.2583745) - committee_pres1 * 0.3083121, eform(hr)
{txt}Confidence interval for formula:
{res}(committee_pres1*0.3083121+1.sendivide#c.committee_pres1*0.2583745)-committee_pres1*0.3083121

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} 1.584886{col 26}{space 2} .3193699{col 37}{space 1}    2.29{col 46}{space 3}0.022{col 54}{space 4} 1.067757{col 67}{space 3} 2.352466
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix model3a = r(table)
{txt}
{com}. mat list model3a
{res}
{txt}model3a[9,1]
               (1)
     b {res} 1.5848855
{txt}    se {res} .31936994
{txt}     z {res} 2.2853093
{txt}pvalue {res}  .0222947
{txt}    ll {res} 1.0677571
{txt}    ul {res} 2.3524659
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         1
{reset}
{com}. 
. *
. *
. *
. *
. 
. 
. 
. *** MODEL G.3B: FULL SAMPLE: |COMMITTEE MEDIAN - PRESIDENT| & PRIORCONFIRM==1 [WEIBULL PARAMETRIC MODEL] ***
. 
. streg  c.committee_pres1##i.sendivide    pressenfloorabsdist   experience_median  committeestaffsize ln_combills_workload   pres_app_m first90 preselection lameduck   kv_workload  polarization   workload  female priorconfirm denied  x_itier_2 x_itier_3 x_itier_4 defense infrastructure social fvra firstrecess secondrecess policy_majagency   i.kbcom_1  i.presrev  if priorconfirm==1, distribution(weibull) vce(cluster kbcom_1)

{col 9}{txt}Failure {bf:_d}: {res}confirmbinary
{col 3}{txt}Analysis time {bf:_t}: {res}legvetdur2plus1
{txt}note: {bf:priorconfirm} omitted because of collinearity.

Fitting constant-only model:
Iteration 0:  Log pseudolikelihood = {res}-2195.1096
{txt}Iteration 1:  Log pseudolikelihood = {res}-2179.3187
{txt}Iteration 2:  Log pseudolikelihood = {res}-2179.3099
{txt}Iteration 3:  Log pseudolikelihood = {res}-2179.3099

{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-2179.3099}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-2094.7636}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-2030.1936}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-2027.6879}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-2027.6452}  
Iteration 5:{space 2}Log pseudolikelihood = {res:-2027.6362}  
Iteration 6:{space 2}Log pseudolikelihood = {res:-2027.6342}  
Iteration 7:{space 2}Log pseudolikelihood = {res:-2027.6337}  
Iteration 8:{space 2}Log pseudolikelihood = {res:-2027.6336}  
Iteration 9:{space 2}Log pseudolikelihood = {res:-2027.6336}  
{res}
{txt}Weibull PH regression

No. of subjects = {res}{ralign 7:1,481}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:1,481}
{txt}No. of failures = {res}{ralign 7:1,022}
{txt}Time at risk    = {res}{ralign 7:159,446}
{col 57}{txt}{lalign 13:{help j_robustsingular##|_new:Wald chi2(18)}} = {res}{ralign 6:.}
{txt}Log pseudolikelihood = {res}-2027.6336{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:.}

{txt}{ralign 81:(Std. err. adjusted for {res:20} clusters in {res:kbcom_1})}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}             _t{col 17}{c |} Haz. ratio{col 29}   std. err.{col 41}      z{col 49}   P>|z|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
committee_pres1 {c |}{col 17}{res}{space 2} .1745685{col 29}{space 2} .1438765{col 40}{space 1}   -2.12{col 49}{space 3}0.034{col 57}{space 4} .0347072{col 70}{space 3} .8780354
{txt}{space 4}1.sendivide {c |}{col 17}{res}{space 2} .2166446{col 29}{space 2} .1018207{col 40}{space 1}   -3.25{col 49}{space 3}0.001{col 57}{space 4} .0862367{col 70}{space 3} .5442565
{txt}{space 15} {c |}
{space 6}sendivide#{c |}
{space 13}c. {c |}
committee_pres1 {c |}
{space 13}1  {c |}{col 17}{res}{space 2} 8.429136{col 29}{space 2} 3.460562{col 40}{space 1}    5.19{col 49}{space 3}0.000{col 57}{space 4} 3.769852{col 70}{space 3} 18.84698
{txt}{space 15} {c |}
pressenfloora~t {c |}{col 17}{res}{space 2} 1.360297{col 29}{space 2} 1.756288{col 40}{space 1}    0.24{col 49}{space 3}0.812{col 57}{space 4} .1083033{col 70}{space 3} 17.08542
{txt}experience_me~n {c |}{col 17}{res}{space 2} 1.008419{col 29}{space 2} .0230521{col 40}{space 1}    0.37{col 49}{space 3}0.714{col 57}{space 4} .9642353{col 70}{space 3} 1.054628
{txt}committeestaf~e {c |}{col 17}{res}{space 2} .9898694{col 29}{space 2} .0048661{col 40}{space 1}   -2.07{col 49}{space 3}0.038{col 57}{space 4} .9803778{col 70}{space 3} .9994529
{txt}ln_combills_w~d {c |}{col 17}{res}{space 2} 1.068591{col 29}{space 2} .2229635{col 40}{space 1}    0.32{col 49}{space 3}0.751{col 57}{space 4} .7099159{col 70}{space 3} 1.608483
{txt}{space 5}pres_app_m {c |}{col 17}{res}{space 2} .9976642{col 29}{space 2} .0054791{col 40}{space 1}   -0.43{col 49}{space 3}0.670{col 57}{space 4} .9869829{col 70}{space 3} 1.008461
{txt}{space 8}first90 {c |}{col 17}{res}{space 2}  1.66225{col 29}{space 2} .2962306{col 40}{space 1}    2.85{col 49}{space 3}0.004{col 57}{space 4} 1.172204{col 70}{space 3} 2.357163
{txt}{space 3}preselection {c |}{col 17}{res}{space 2} .7029111{col 29}{space 2} .0847115{col 40}{space 1}   -2.93{col 49}{space 3}0.003{col 57}{space 4} .5550316{col 70}{space 3} .8901908
{txt}{space 7}lameduck {c |}{col 17}{res}{space 2} 1.170209{col 29}{space 2} .0998266{col 40}{space 1}    1.84{col 49}{space 3}0.065{col 57}{space 4} .9900344{col 70}{space 3} 1.383173
{txt}{space 4}kv_workload {c |}{col 17}{res}{space 2} .9999621{col 29}{space 2} .0000546{col 40}{space 1}   -0.70{col 49}{space 3}0.487{col 57}{space 4} .9998552{col 70}{space 3} 1.000069
{txt}{space 3}polarization {c |}{col 17}{res}{space 2} .0103911{col 29}{space 2} .0270097{col 40}{space 1}   -1.76{col 49}{space 3}0.079{col 57}{space 4} .0000637{col 70}{space 3} 1.695088
{txt}{space 7}workload {c |}{col 17}{res}{space 2} 1.002082{col 29}{space 2} .0018813{col 40}{space 1}    1.11{col 49}{space 3}0.268{col 57}{space 4} .9984018{col 70}{space 3} 1.005776
{txt}{space 9}female {c |}{col 17}{res}{space 2}  1.05305{col 29}{space 2} .0919472{col 40}{space 1}    0.59{col 49}{space 3}0.554{col 57}{space 4} .8874137{col 70}{space 3} 1.249602
{txt}{space 3}priorconfirm {c |}{col 17}{res}{space 2}        1{col 29}{txt}  (omitted)
{space 9}denied {c |}{col 17}{res}{space 2} .5733919{col 29}{space 2} .0957528{col 40}{space 1}   -3.33{col 49}{space 3}0.001{col 57}{space 4} .4133389{col 70}{space 3} .7954206
{txt}{space 6}x_itier_2 {c |}{col 17}{res}{space 2} .8786155{col 29}{space 2} .1054813{col 40}{space 1}   -1.08{col 49}{space 3}0.281{col 57}{space 4} .6943984{col 70}{space 3} 1.111704
{txt}{space 6}x_itier_3 {c |}{col 17}{res}{space 2} .6036989{col 29}{space 2} .1224991{col 40}{space 1}   -2.49{col 49}{space 3}0.013{col 57}{space 4} .4056014{col 70}{space 3} .8985481
{txt}{space 6}x_itier_4 {c |}{col 17}{res}{space 2} .6379479{col 29}{space 2} .0705899{col 40}{space 1}   -4.06{col 49}{space 3}0.000{col 57}{space 4} .5135687{col 70}{space 3} .7924501
{txt}{space 8}defense {c |}{col 17}{res}{space 2} .9661266{col 29}{space 2} .1546896{col 40}{space 1}   -0.22{col 49}{space 3}0.830{col 57}{space 4} .7059037{col 70}{space 3} 1.322278
{txt}{space 1}infrastructure {c |}{col 17}{res}{space 2} .8158233{col 29}{space 2} .1252178{col 40}{space 1}   -1.33{col 49}{space 3}0.185{col 57}{space 4} .6038766{col 70}{space 3} 1.102158
{txt}{space 9}social {c |}{col 17}{res}{space 2} .9239236{col 29}{space 2} .1684142{col 40}{space 1}   -0.43{col 49}{space 3}0.664{col 57}{space 4} .6463649{col 70}{space 3}  1.32067
{txt}{space 11}fvra {c |}{col 17}{res}{space 2} 1.042571{col 29}{space 2} .1450595{col 40}{space 1}    0.30{col 49}{space 3}0.764{col 57}{space 4} .7937292{col 70}{space 3} 1.369426
{txt}{space 4}firstrecess {c |}{col 17}{res}{space 2} .9655126{col 29}{space 2} .1164902{col 40}{space 1}   -0.29{col 49}{space 3}0.771{col 57}{space 4} .7621834{col 70}{space 3} 1.223084
{txt}{space 3}secondrecess {c |}{col 17}{res}{space 2} .8285708{col 29}{space 2} .1099136{col 40}{space 1}   -1.42{col 49}{space 3}0.156{col 57}{space 4}  .638872{col 70}{space 3} 1.074596
{txt}policy_majage~y {c |}{col 17}{res}{space 2} 1.086449{col 29}{space 2} .1343544{col 40}{space 1}    0.67{col 49}{space 3}0.503{col 57}{space 4} .8526021{col 70}{space 3} 1.384433
{txt}{space 15} {c |}
{space 8}kbcom_1 {c |}
{space 13}2  {c |}{col 17}{res}{space 2} .7885982{col 29}{space 2} .1513348{col 40}{space 1}   -1.24{col 49}{space 3}0.216{col 57}{space 4} .5413862{col 70}{space 3} 1.148694
{txt}{space 13}3  {c |}{col 17}{res}{space 2} .6002955{col 29}{space 2}  .076758{col 40}{space 1}   -3.99{col 49}{space 3}0.000{col 57}{space 4} .4672232{col 70}{space 3} .7712688
{txt}{space 13}4  {c |}{col 17}{res}{space 2}  1.88877{col 29}{space 2} .5794009{col 40}{space 1}    2.07{col 49}{space 3}0.038{col 57}{space 4} 1.035294{col 70}{space 3} 3.445835
{txt}{space 13}5  {c |}{col 17}{res}{space 2} .9229859{col 29}{space 2} .2004642{col 40}{space 1}   -0.37{col 49}{space 3}0.712{col 57}{space 4} .6030061{col 70}{space 3}  1.41276
{txt}{space 13}6  {c |}{col 17}{res}{space 2} 1.235579{col 29}{space 2} .2730749{col 40}{space 1}    0.96{col 49}{space 3}0.338{col 57}{space 4} .8012108{col 70}{space 3} 1.905436
{txt}{space 13}7  {c |}{col 17}{res}{space 2} .7675846{col 29}{space 2} .1030032{col 40}{space 1}   -1.97{col 49}{space 3}0.049{col 57}{space 4} .5900684{col 70}{space 3} .9985048
{txt}{space 13}8  {c |}{col 17}{res}{space 2} .7523951{col 29}{space 2} .3171362{col 40}{space 1}   -0.67{col 49}{space 3}0.500{col 57}{space 4} .3293538{col 70}{space 3} 1.718816
{txt}{space 13}9  {c |}{col 17}{res}{space 2} .5390414{col 29}{space 2} .0853148{col 40}{space 1}   -3.90{col 49}{space 3}0.000{col 57}{space 4} .3952768{col 70}{space 3} .7350942
{txt}{space 12}10  {c |}{col 17}{res}{space 2} .7267792{col 29}{space 2} .1802535{col 40}{space 1}   -1.29{col 49}{space 3}0.198{col 57}{space 4} .4469821{col 70}{space 3} 1.181721
{txt}{space 12}11  {c |}{col 17}{res}{space 2} .7099021{col 29}{space 2}    .2754{col 40}{space 1}   -0.88{col 49}{space 3}0.377{col 57}{space 4} .3318811{col 70}{space 3} 1.518498
{txt}{space 12}12  {c |}{col 17}{res}{space 2} .8319731{col 29}{space 2} .2456055{col 40}{space 1}   -0.62{col 49}{space 3}0.533{col 57}{space 4} .4664739{col 70}{space 3} 1.483854
{txt}{space 12}13  {c |}{col 17}{res}{space 2}  .309287{col 29}{space 2} .0697143{col 40}{space 1}   -5.21{col 49}{space 3}0.000{col 57}{space 4} .1988374{col 70}{space 3} .4810888
{txt}{space 12}14  {c |}{col 17}{res}{space 2} .7481164{col 29}{space 2}  .436166{col 40}{space 1}   -0.50{col 49}{space 3}0.619{col 57}{space 4} .2386177{col 70}{space 3} 2.345502
{txt}{space 12}15  {c |}{col 17}{res}{space 2} .7758755{col 29}{space 2}  .320345{col 40}{space 1}   -0.61{col 49}{space 3}0.539{col 57}{space 4} .3454191{col 70}{space 3} 1.742761
{txt}{space 12}16  {c |}{col 17}{res}{space 2} .7276924{col 29}{space 2} .2155805{col 40}{space 1}   -1.07{col 49}{space 3}0.283{col 57}{space 4} .4071716{col 70}{space 3} 1.300523
{txt}{space 12}17  {c |}{col 17}{res}{space 2} .3778637{col 29}{space 2}  .065072{col 40}{space 1}   -5.65{col 49}{space 3}0.000{col 57}{space 4} .2696183{col 70}{space 3} .5295669
{txt}{space 12}18  {c |}{col 17}{res}{space 2} 1.917076{col 29}{space 2}  .903961{col 40}{space 1}    1.38{col 49}{space 3}0.168{col 57}{space 4} .7608014{col 70}{space 3}  4.83067
{txt}{space 12}19  {c |}{col 17}{res}{space 2} 1.42e-06{col 29}{space 2} 1.50e-06{col 40}{space 1}  -12.73{col 49}{space 3}0.000{col 57}{space 4} 1.78e-07{col 70}{space 3} .0000113
{txt}{space 12}20  {c |}{col 17}{res}{space 2} .5468971{col 29}{space 2} .1220568{col 40}{space 1}   -2.70{col 49}{space 3}0.007{col 57}{space 4} .3531295{col 70}{space 3} .8469881
{txt}{space 15} {c |}
{space 8}presrev {c |}
{space 13}2  {c |}{col 17}{res}{space 2}  2.30754{col 29}{space 2} .6733738{col 40}{space 1}    2.87{col 49}{space 3}0.004{col 57}{space 4} 1.302435{col 70}{space 3} 4.088295
{txt}{space 13}3  {c |}{col 17}{res}{space 2} 1.903775{col 29}{space 2} .7013502{col 40}{space 1}    1.75{col 49}{space 3}0.081{col 57}{space 4} .9247689{col 70}{space 3} 3.919206
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 1.520519{col 29}{space 2} 1.068497{col 40}{space 1}    0.60{col 49}{space 3}0.551{col 57}{space 4} .3835627{col 70}{space 3} 6.027637
{txt}{space 13}5  {c |}{col 17}{res}{space 2} 1.057692{col 29}{space 2}  .510314{col 40}{space 1}    0.12{col 49}{space 3}0.907{col 57}{space 4} .4108401{col 70}{space 3}  2.72299
{txt}{space 13}6  {c |}{col 17}{res}{space 2} 1.162617{col 29}{space 2} .8363499{col 40}{space 1}    0.21{col 49}{space 3}0.834{col 57}{space 4}  .283863{col 70}{space 3} 4.761724
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} 1.025469{col 29}{space 2} 1.948414{col 40}{space 1}    0.01{col 49}{space 3}0.989{col 57}{space 4} .0247526{col 70}{space 3} 42.48393
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}/ln_p {c |}{col 17}{res}{space 2}-.0319375{col 29}{space 2} .0288113{col 40}{space 1}   -1.11{col 49}{space 3}0.268{col 57}{space 4}-.0884066{col 70}{space 3} .0245315
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
              p {c |}{col 17}{res}{space 2} .9685671{col 29}{space 2} .0279057{col 57}{space 4} .9153886{col 70}{space 3} 1.024835
{txt}            1/p {c |}{col 17}{res}{space 2} 1.032453{col 29}{space 2} .0297463{col 57}{space 4} .9757669{col 70}{space 3} 1.092432
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {bf:_cons} estimates baseline hazard{txt}.{p_end}

{com}. *
. 
. * DESCRIPTIVE STATISTICS FOR EACH PARTISAN CONTROL REGIME [NOTE: THESE VARY ACROSS SUBSAMPLES OF INTEREST] *
. sum wSenComm_committee_pres1 if e(sample) & sendivide==0, detail

                  {txt}wSenComm_committee_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}-.5386078      -.5386078
{txt} 5%    {res} -.412061      -.5386078
{txt}10%    {res}-.4026805      -.5386078       {txt}Obs         {res}        713
{txt}25%    {res}-.3220448      -.5386078       {txt}Sum of wgt. {res}        713

{txt}50%    {res} -.132869                      {txt}Mean          {res}-.1219668
                        {txt}Largest       Std. dev.     {res} .2250392
{txt}75%    {res} .1149552       .3563195
{txt}90%    {res} .1603195       .3563195       {txt}Variance      {res} .0506426
{txt}95%    {res} .2121217       .3563195       {txt}Skewness      {res} .2151789
{txt}99%    {res} .3387852       .4655938       {txt}Kurtosis      {res} 1.889663
{txt}
{com}. sum wSenComm_committee_pres1 if e(sample) & sendivide==1, detail

                  {txt}wSenComm_committee_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}-.1966079      -.2916805
{txt} 5%    {res}-.1966079      -.1966079
{txt}10%    {res}-.0977183      -.1966079       {txt}Obs         {res}        768
{txt}25%    {res} .0419552      -.1966079       {txt}Sum of wgt. {res}        768

{txt}50%    {res} .1929552                      {txt}Mean          {res} .1588885
                        {txt}Largest       Std. dev.     {res} .1837394
{txt}75%    {res} .2885807        .490939
{txt}90%    {res} .3931217        .490939       {txt}Variance      {res} .0337602
{txt}95%    {res} .4655938        .490939       {txt}Skewness      {res}-.1952754
{txt}99%    {res} .4706168        .490939       {txt}Kurtosis      {res} 2.343359
{txt}
{com}. 
. 
. 
. ** CONDITIONAL COEFFICIENT ANALYSIS TESTS: DIRECTION [+] ** 
. 
. * DIFFERENCE BETWEEN DIVIDED AND UNIFIED PARTISAN CONTROL OF SENATE & PRESIDENCY: INTERQUARTILE UNIT CHANGE IN "wSenComm_committee_pres1"  *
. lincomest (committee_pres1 * 0.437 +  1.sendivide#c.committee_pres1 * 0.2466255) - committee_pres1 * 0.437, eform(hr)
{txt}Confidence interval for formula:
{res}(committee_pres1*0.437+1.sendivide#c.committee_pres1*0.2466255)-committee_pres1*0.437

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} 1.691694{col 26}{space 2} .1712865{col 37}{space 1}    5.19{col 46}{space 3}0.000{col 54}{space 4} 1.387191{col 67}{space 3} 2.063038
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix model3b = r(table)
{txt}
{com}. mat list model3b
{res}
{txt}model3b[9,1]
               (1)
     b {res} 1.6916936
{txt}    se {res} .17128653
{txt}     z {res} 5.1923195
{txt}pvalue {res} 2.077e-07
{txt}    ll {res}  1.387191
{txt}    ul {res} 2.0630376
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         1
{reset}
{com}. 
. 
. 
. ******************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. 
. 
. *** MODEL G.4A: FULL SAMPLE: |COMMITTEE CHAIR - PRESIDENT| & PRIORCONFIRM==0 [WEIBULL PARAMETRIC MODEL] ***
. 
. stcox  c.chair_pres1##i.sendivide   pressenfloorabsdist   chair_experience_1  committeestaffsize ln_combills_workload   pres_app_m first90 preselection lameduck   kv_workload  polarization   workload  female priorconfirm denied  x_itier_2 x_itier_3 x_itier_4 defense infrastructure social fvra firstrecess secondrecess policy_majagency    i.kbcom_1  i.presrev if priorconfirm==0, vce(cluster kbcom_1)

{col 9}{txt}Failure {bf:_d}: {res}confirmbinary
{col 3}{txt}Analysis time {bf:_t}: {res}legvetdur2plus1

{txt}note: {bf:priorconfirm} omitted because of collinearity.
Iteration 0:  Log pseudolikelihood = {res}-50063.777
{txt}Iteration 1:  Log pseudolikelihood = {res}-49900.902
{txt}Iteration 2:  Log pseudolikelihood = {res}-49283.168
{txt}Iteration 3:  Log pseudolikelihood = {res}-49231.988
{txt}Iteration 4:  Log pseudolikelihood = {res}-49230.759
{txt}Iteration 5:  Log pseudolikelihood = {res}-49230.757
{txt}Refining estimates:
Iteration 0:  Log pseudolikelihood = {res}-49230.757

{txt}Cox regression with Breslow method for ties

No. of subjects = {res}{ralign 7:8,398}{col 56}{txt}{lalign 13:Number of obs} = {res}{ralign 7:8,398}
{txt}No. of failures = {res}{ralign 7:6,054}
{txt}Time at risk    = {res}{ralign 7:828,365}
{col 56}{txt}{lalign 13:Wald chi2({res:19})} = {res}{ralign 7:8090.77}
{txt}Log pseudolikelihood = {res}-49230.757{col 56}{txt}{lalign 13:Prob > chi2} = {res}{ralign 7:0.0000}

{txt}{ralign 81:(Std. err. adjusted for {res:20} clusters in {res:kbcom_1})}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}             _t{col 17}{c |} Haz. ratio{col 29}   std. err.{col 41}      z{col 49}   P>|z|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}chair_pres1 {c |}{col 17}{res}{space 2} .8028725{col 29}{space 2} .2160943{col 40}{space 1}   -0.82{col 49}{space 3}0.415{col 57}{space 4} .4737448{col 70}{space 3} 1.360657
{txt}{space 4}1.sendivide {c |}{col 17}{res}{space 2} .3763423{col 29}{space 2}  .139158{col 40}{space 1}   -2.64{col 49}{space 3}0.008{col 57}{space 4} .1823219{col 70}{space 3} .7768321
{txt}{space 15} {c |}
{space 6}sendivide#{c |}
{space 2}c.chair_pres1 {c |}
{space 13}1  {c |}{col 17}{res}{space 2} 2.700683{col 29}{space 2} 1.100155{col 40}{space 1}    2.44{col 49}{space 3}0.015{col 57}{space 4}  1.21542{col 70}{space 3}  6.00096
{txt}{space 15} {c |}
pressenfloora~t {c |}{col 17}{res}{space 2}  .689724{col 29}{space 2} .4406142{col 40}{space 1}   -0.58{col 49}{space 3}0.561{col 57}{space 4} .1971991{col 70}{space 3}  2.41238
{txt}chair_experie~1 {c |}{col 17}{res}{space 2} 1.002972{col 29}{space 2} .0033227{col 40}{space 1}    0.90{col 49}{space 3}0.370{col 57}{space 4} .9964802{col 70}{space 3} 1.009505
{txt}committeestaf~e {c |}{col 17}{res}{space 2} .9922702{col 29}{space 2} .0045656{col 40}{space 1}   -1.69{col 49}{space 3}0.092{col 57}{space 4}  .983362{col 70}{space 3} 1.001259
{txt}ln_combills_w~d {c |}{col 17}{res}{space 2} .8259249{col 29}{space 2} .0765658{col 40}{space 1}   -2.06{col 49}{space 3}0.039{col 57}{space 4} .6887023{col 70}{space 3} .9904888
{txt}{space 5}pres_app_m {c |}{col 17}{res}{space 2} 1.003524{col 29}{space 2} .0020949{col 40}{space 1}    1.68{col 49}{space 3}0.092{col 57}{space 4} .9994261{col 70}{space 3} 1.007638
{txt}{space 8}first90 {c |}{col 17}{res}{space 2} 2.983058{col 29}{space 2} .2616605{col 40}{space 1}   12.46{col 49}{space 3}0.000{col 57}{space 4} 2.511876{col 70}{space 3} 3.542626
{txt}{space 3}preselection {c |}{col 17}{res}{space 2} .7080065{col 29}{space 2} .0489247{col 40}{space 1}   -5.00{col 49}{space 3}0.000{col 57}{space 4}  .618326{col 70}{space 3}  .810694
{txt}{space 7}lameduck {c |}{col 17}{res}{space 2} .8275227{col 29}{space 2} .0647097{col 40}{space 1}   -2.42{col 49}{space 3}0.015{col 57}{space 4}  .709935{col 70}{space 3} .9645867
{txt}{space 4}kv_workload {c |}{col 17}{res}{space 2} 1.000009{col 29}{space 2} .0000338{col 40}{space 1}    0.28{col 49}{space 3}0.779{col 57}{space 4} .9999433{col 70}{space 3} 1.000076
{txt}{space 3}polarization {c |}{col 17}{res}{space 2} .0262249{col 29}{space 2}  .035757{col 40}{space 1}   -2.67{col 49}{space 3}0.008{col 57}{space 4} .0018119{col 70}{space 3} .3795819
{txt}{space 7}workload {c |}{col 17}{res}{space 2}  1.00181{col 29}{space 2} .0015628{col 40}{space 1}    1.16{col 49}{space 3}0.246{col 57}{space 4} .9987513{col 70}{space 3} 1.004877
{txt}{space 9}female {c |}{col 17}{res}{space 2} .9891279{col 29}{space 2} .0434077{col 40}{space 1}   -0.25{col 49}{space 3}0.803{col 57}{space 4} .9076067{col 70}{space 3} 1.077971
{txt}{space 3}priorconfirm {c |}{col 17}{res}{space 2}        1{col 29}{txt}  (omitted)
{space 9}denied {c |}{col 17}{res}{space 2}  .668646{col 29}{space 2} .0726658{col 40}{space 1}   -3.70{col 49}{space 3}0.000{col 57}{space 4} .5403699{col 70}{space 3} .8273731
{txt}{space 6}x_itier_2 {c |}{col 17}{res}{space 2} .9563546{col 29}{space 2} .0488684{col 40}{space 1}   -0.87{col 49}{space 3}0.382{col 57}{space 4} .8652145{col 70}{space 3} 1.057095
{txt}{space 6}x_itier_3 {c |}{col 17}{res}{space 2} .8320414{col 29}{space 2} .1562259{col 40}{space 1}   -0.98{col 49}{space 3}0.327{col 57}{space 4} .5758661{col 70}{space 3} 1.202177
{txt}{space 6}x_itier_4 {c |}{col 17}{res}{space 2} .8314942{col 29}{space 2}  .109339{col 40}{space 1}   -1.40{col 49}{space 3}0.161{col 57}{space 4} .6425824{col 70}{space 3} 1.075944
{txt}{space 8}defense {c |}{col 17}{res}{space 2}  1.01284{col 29}{space 2} .0749161{col 40}{space 1}    0.17{col 49}{space 3}0.863{col 57}{space 4}  .876154{col 70}{space 3} 1.170849
{txt}{space 1}infrastructure {c |}{col 17}{res}{space 2} .9645026{col 29}{space 2} .0794036{col 40}{space 1}   -0.44{col 49}{space 3}0.661{col 57}{space 4} .8207812{col 70}{space 3}  1.13339
{txt}{space 9}social {c |}{col 17}{res}{space 2}  .938358{col 29}{space 2} .0699992{col 40}{space 1}   -0.85{col 49}{space 3}0.394{col 57}{space 4} .8107203{col 70}{space 3} 1.086091
{txt}{space 11}fvra {c |}{col 17}{res}{space 2} 1.215424{col 29}{space 2} .0847507{col 40}{space 1}    2.80{col 49}{space 3}0.005{col 57}{space 4} 1.060167{col 70}{space 3} 1.393418
{txt}{space 4}firstrecess {c |}{col 17}{res}{space 2}   .96175{col 29}{space 2} .0439513{col 40}{space 1}   -0.85{col 49}{space 3}0.393{col 57}{space 4} .8793523{col 70}{space 3} 1.051869
{txt}{space 3}secondrecess {c |}{col 17}{res}{space 2} .7492737{col 29}{space 2}  .060824{col 40}{space 1}   -3.56{col 49}{space 3}0.000{col 57}{space 4}  .639061{col 70}{space 3} .8784937
{txt}policy_majage~y {c |}{col 17}{res}{space 2} 1.284525{col 29}{space 2} .0874338{col 40}{space 1}    3.68{col 49}{space 3}0.000{col 57}{space 4} 1.124097{col 70}{space 3} 1.467848
{txt}{space 15} {c |}
{space 8}kbcom_1 {c |}
{space 13}2  {c |}{col 17}{res}{space 2} 1.080604{col 29}{space 2} .0975658{col 40}{space 1}    0.86{col 49}{space 3}0.391{col 57}{space 4} .9053432{col 70}{space 3} 1.289793
{txt}{space 13}3  {c |}{col 17}{res}{space 2} 1.083981{col 29}{space 2} .0702114{col 40}{space 1}    1.24{col 49}{space 3}0.213{col 57}{space 4} .9547461{col 70}{space 3} 1.230709
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 3.639333{col 29}{space 2} .4415914{col 40}{space 1}   10.65{col 49}{space 3}0.000{col 57}{space 4} 2.869051{col 70}{space 3} 4.616421
{txt}{space 13}5  {c |}{col 17}{res}{space 2} 1.457982{col 29}{space 2} .2379067{col 40}{space 1}    2.31{col 49}{space 3}0.021{col 57}{space 4} 1.058905{col 70}{space 3} 2.007462
{txt}{space 13}6  {c |}{col 17}{res}{space 2}  1.78872{col 29}{space 2} .2516791{col 40}{space 1}    4.13{col 49}{space 3}0.000{col 57}{space 4} 1.357611{col 70}{space 3} 2.356728
{txt}{space 13}7  {c |}{col 17}{res}{space 2} 1.289802{col 29}{space 2} .1306636{col 40}{space 1}    2.51{col 49}{space 3}0.012{col 57}{space 4} 1.057528{col 70}{space 3} 1.573092
{txt}{space 13}8  {c |}{col 17}{res}{space 2} 1.199687{col 29}{space 2} .3508422{col 40}{space 1}    0.62{col 49}{space 3}0.534{col 57}{space 4} .6762984{col 70}{space 3} 2.128126
{txt}{space 13}9  {c |}{col 17}{res}{space 2} 1.139996{col 29}{space 2}  .140756{col 40}{space 1}    1.06{col 49}{space 3}0.289{col 57}{space 4} .8949625{col 70}{space 3} 1.452117
{txt}{space 12}10  {c |}{col 17}{res}{space 2} .8847041{col 29}{space 2} .2363967{col 40}{space 1}   -0.46{col 49}{space 3}0.647{col 57}{space 4} .5240266{col 70}{space 3} 1.493629
{txt}{space 12}11  {c |}{col 17}{res}{space 2} 1.481634{col 29}{space 2} .4073521{col 40}{space 1}    1.43{col 49}{space 3}0.153{col 57}{space 4} .8644034{col 70}{space 3} 2.539601
{txt}{space 12}12  {c |}{col 17}{res}{space 2} 1.424419{col 29}{space 2} .5559268{col 40}{space 1}    0.91{col 49}{space 3}0.365{col 57}{space 4} .6628697{col 70}{space 3} 3.060888
{txt}{space 12}13  {c |}{col 17}{res}{space 2} .8368383{col 29}{space 2} .0838085{col 40}{space 1}   -1.78{col 49}{space 3}0.075{col 57}{space 4}  .687693{col 70}{space 3}  1.01833
{txt}{space 12}14  {c |}{col 17}{res}{space 2} 1.084523{col 29}{space 2} .2236715{col 40}{space 1}    0.39{col 49}{space 3}0.694{col 57}{space 4} .7239151{col 70}{space 3} 1.624764
{txt}{space 12}15  {c |}{col 17}{res}{space 2} 2.074593{col 29}{space 2} .8547553{col 40}{space 1}    1.77{col 49}{space 3}0.077{col 57}{space 4} .9251845{col 70}{space 3} 4.651975
{txt}{space 12}16  {c |}{col 17}{res}{space 2} 1.526708{col 29}{space 2} .4808642{col 40}{space 1}    1.34{col 49}{space 3}0.179{col 57}{space 4} .8234828{col 70}{space 3} 2.830461
{txt}{space 12}17  {c |}{col 17}{res}{space 2} .6719495{col 29}{space 2} .1036743{col 40}{space 1}   -2.58{col 49}{space 3}0.010{col 57}{space 4} .4965988{col 70}{space 3}  .909217
{txt}{space 12}18  {c |}{col 17}{res}{space 2}  .630572{col 29}{space 2} .1627182{col 40}{space 1}   -1.79{col 49}{space 3}0.074{col 57}{space 4} .3802623{col 70}{space 3} 1.045649
{txt}{space 12}19  {c |}{col 17}{res}{space 2} .5521822{col 29}{space 2} .0562624{col 40}{space 1}   -5.83{col 49}{space 3}0.000{col 57}{space 4} .4522229{col 70}{space 3} .6742365
{txt}{space 12}20  {c |}{col 17}{res}{space 2} .9646997{col 29}{space 2} .0950716{col 40}{space 1}   -0.36{col 49}{space 3}0.715{col 57}{space 4}  .795254{col 70}{space 3}  1.17025
{txt}{space 15} {c |}
{space 8}presrev {c |}
{space 13}2  {c |}{col 17}{res}{space 2} 1.599344{col 29}{space 2} .3203167{col 40}{space 1}    2.34{col 49}{space 3}0.019{col 57}{space 4} 1.080098{col 70}{space 3} 2.368211
{txt}{space 13}3  {c |}{col 17}{res}{space 2} 1.600804{col 29}{space 2}  .504362{col 40}{space 1}    1.49{col 49}{space 3}0.135{col 57}{space 4} .8632807{col 70}{space 3} 2.968414
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 1.582716{col 29}{space 2} .5018579{col 40}{space 1}    1.45{col 49}{space 3}0.148{col 57}{space 4} .8501561{col 70}{space 3} 2.946507
{txt}{space 13}5  {c |}{col 17}{res}{space 2} 1.326486{col 29}{space 2} .5380534{col 40}{space 1}    0.70{col 49}{space 3}0.486{col 57}{space 4} .5990123{col 70}{space 3} 2.937445
{txt}{space 13}6  {c |}{col 17}{res}{space 2} 1.309837{col 29}{space 2} .5540861{col 40}{space 1}    0.64{col 49}{space 3}0.523{col 57}{space 4} .5716664{col 70}{space 3} 3.001178
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. 
. * DESCRIPTIVE STATISTICS FOR EACH PARTISAN CONTROL REGIME [NOTE: THESE VARY ACROSS SUBSAMPLES OF INTEREST] *
. sum wSenComm_chair_pres1 if e(sample) & sendivide==0, detail

                    {txt}wSenComm_chair_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}-.7163319      -.7163319
{txt} 5%    {res}-.5493055      -.7163319
{txt}10%    {res}-.5251514      -.7163319       {txt}Obs         {res}      4,475
{txt}25%    {res}-.4552139      -.7163319       {txt}Sum of wgt. {res}      4,475

{txt}50%    {res}-.3661785                      {txt}Mean          {res}-.3145722
                        {txt}Largest       Std. dev.     {res} .2565557
{txt}75%    {res}-.2196792       .6940686
{txt}90%    {res}-.0447927       .6940686       {txt}Variance      {res} .0658208
{txt}95%    {res}  .208236       .6940686       {txt}Skewness      {res} 1.887141
{txt}99%    {res} .6122074       .6940686       {txt}Kurtosis      {res} 7.304456
{txt}
{com}. sum wSenComm_chair_pres1 if e(sample) & sendivide==1, detail

                    {txt}wSenComm_chair_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}-.2693319      -.7163319
{txt} 5%    {res}-.0833319       -.411764
{txt}10%    {res} .0763208      -.3632139       {txt}Obs         {res}      3,923
{txt}25%    {res} .2632073      -.3632139       {txt}Sum of wgt. {res}      3,923

{txt}50%    {res} .3612073                      {txt}Mean          {res} .3567821
                        {txt}Largest       Std. dev.     {res} .2106762
{txt}75%    {res} .4938942       .7534087
{txt}90%    {res} .6122074       .7534087       {txt}Variance      {res} .0443844
{txt}95%    {res} .6940686       .7534087       {txt}Skewness      {res}-.7035733
{txt}99%    {res} .7534087       .8284615       {txt}Kurtosis      {res} 3.791322
{txt}
{com}. 
. 
. 
. ** CONDITIONAL COEFFICIENT ANALYSIS TESTS: DIRECTION [+] ** 
. 
. * DIFFERENCE BETWEEN DIVIDED AND UNIFIED PARTISAN CONTROL OF SENATE & PRESIDENCY: INTERQUARTILE UNIT CHANGE IN "wSenComm_chair_pres1"  *
. lincomest (chair_pres1 * 0.2355347 +  1.sendivide#c.chair_pres1 * 0.2306869) - chair_pres1 * 0.2355347, eform(hr)
{txt}Confidence interval for formula:
{res}(chair_pres1*0.2355347+1.sendivide#c.chair_pres1*0.2306869)-chair_pres1*0.2355347

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} 1.257579{col 26}{space 2} .1181786{col 37}{space 1}    2.44{col 46}{space 3}0.015{col 54}{space 4} 1.046033{col 67}{space 3} 1.511908
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix model4a = r(table)
{txt}
{com}. mat list model4a
{res}
{txt}model4a[9,1]
               (1)
     b {res} 1.2575791
{txt}    se {res} .11817857
{txt}     z {res}  2.438874
{txt}pvalue {res}  .0147331
{txt}    ll {res} 1.0460327
{txt}    ul {res} 1.5119078
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         1
{reset}
{com}. 
. *
. *
. *
. *
. 
. 
. 
. 
. *** MODEL G.4B: FULL SAMPLE: |COMMITTEE CHAIR - PRESIDENT| & PRIORCONFIRM==1 [WEIBULL PARAMETRIC MODEL] ***
. 
. streg  c.chair_pres1##i.sendivide   pressenfloorabsdist   chair_experience_1  committeestaffsize ln_combills_workload   pres_app_m first90 preselection lameduck   kv_workload  polarization   workload  female priorconfirm denied  x_itier_2 x_itier_3 x_itier_4 defense infrastructure social fvra firstrecess secondrecess policy_majagency      i.kbcom_1  i.presrev if priorconfirm==1,  distribution(weibull) vce(cluster kbcom_1)

{col 9}{txt}Failure {bf:_d}: {res}confirmbinary
{col 3}{txt}Analysis time {bf:_t}: {res}legvetdur2plus1
{txt}note: {bf:priorconfirm} omitted because of collinearity.

Fitting constant-only model:
Iteration 0:  Log pseudolikelihood = {res}-2195.1096
{txt}Iteration 1:  Log pseudolikelihood = {res}-2179.3187
{txt}Iteration 2:  Log pseudolikelihood = {res}-2179.3099
{txt}Iteration 3:  Log pseudolikelihood = {res}-2179.3099

{txt}Fitting full model:
{res}{txt}Iteration 0:{space 2}Log pseudolikelihood = {res:-2179.3099}  
Iteration 1:{space 2}Log pseudolikelihood = {res:-2098.1446}  
Iteration 2:{space 2}Log pseudolikelihood = {res:-2032.8015}  
Iteration 3:{space 2}Log pseudolikelihood = {res:-2030.2046}  
Iteration 4:{space 2}Log pseudolikelihood = {res:-2030.1622}  
Iteration 5:{space 2}Log pseudolikelihood = {res:-2030.1533}  
Iteration 6:{space 2}Log pseudolikelihood = {res:-2030.1512}  
Iteration 7:{space 2}Log pseudolikelihood = {res:-2030.1507}  
Iteration 8:{space 2}Log pseudolikelihood = {res:-2030.1506}  
Iteration 9:{space 2}Log pseudolikelihood = {res:-2030.1506}  
{res}
{txt}Weibull PH regression

No. of subjects = {res}{ralign 7:1,481}{col 57}{txt}{lalign 13:Number of obs} = {res}{ralign 6:1,481}
{txt}No. of failures = {res}{ralign 7:1,022}
{txt}Time at risk    = {res}{ralign 7:159,446}
{col 57}{txt}{lalign 13:{help j_robustsingular##|_new:Wald chi2(18)}} = {res}{ralign 6:.}
{txt}Log pseudolikelihood = {res}-2030.1506{col 57}{txt}{lalign 13:Prob > chi2} = {res}{ralign 6:.}

{txt}{ralign 81:(Std. err. adjusted for {res:20} clusters in {res:kbcom_1})}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}             _t{col 17}{c |} Haz. ratio{col 29}   std. err.{col 41}      z{col 49}   P>|z|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}chair_pres1 {c |}{col 17}{res}{space 2} .6981336{col 29}{space 2} .3780018{col 40}{space 1}   -0.66{col 49}{space 3}0.507{col 57}{space 4} .2415787{col 70}{space 3} 2.017522
{txt}{space 4}1.sendivide {c |}{col 17}{res}{space 2} .4688736{col 29}{space 2} .2141592{col 40}{space 1}   -1.66{col 49}{space 3}0.097{col 57}{space 4} .1915435{col 70}{space 3} 1.147742
{txt}{space 15} {c |}
{space 6}sendivide#{c |}
{space 2}c.chair_pres1 {c |}
{space 13}1  {c |}{col 17}{res}{space 2} 1.946618{col 29}{space 2} .8695064{col 40}{space 1}    1.49{col 49}{space 3}0.136{col 57}{space 4} .8110914{col 70}{space 3} 4.671879
{txt}{space 15} {c |}
pressenfloora~t {c |}{col 17}{res}{space 2} .6934016{col 29}{space 2} .7019822{col 40}{space 1}   -0.36{col 49}{space 3}0.718{col 57}{space 4} .0953345{col 70}{space 3} 5.043357
{txt}chair_experie~1 {c |}{col 17}{res}{space 2} 1.013862{col 29}{space 2} .0046918{col 40}{space 1}    2.97{col 49}{space 3}0.003{col 57}{space 4} 1.004708{col 70}{space 3}   1.0231
{txt}committeestaf~e {c |}{col 17}{res}{space 2} .9908012{col 29}{space 2} .0048643{col 40}{space 1}   -1.88{col 49}{space 3}0.060{col 57}{space 4} .9813131{col 70}{space 3} 1.000381
{txt}ln_combills_w~d {c |}{col 17}{res}{space 2} 1.020091{col 29}{space 2} .2051148{col 40}{space 1}    0.10{col 49}{space 3}0.921{col 57}{space 4} .6878334{col 70}{space 3} 1.512844
{txt}{space 5}pres_app_m {c |}{col 17}{res}{space 2} .9979412{col 29}{space 2} .0062483{col 40}{space 1}   -0.33{col 49}{space 3}0.742{col 57}{space 4} .9857695{col 70}{space 3} 1.010263
{txt}{space 8}first90 {c |}{col 17}{res}{space 2} 1.768513{col 29}{space 2} .3227136{col 40}{space 1}    3.12{col 49}{space 3}0.002{col 57}{space 4} 1.236754{col 70}{space 3} 2.528909
{txt}{space 3}preselection {c |}{col 17}{res}{space 2} .6885437{col 29}{space 2} .0777667{col 40}{space 1}   -3.30{col 49}{space 3}0.001{col 57}{space 4} .5518151{col 70}{space 3} .8591508
{txt}{space 7}lameduck {c |}{col 17}{res}{space 2} 1.152307{col 29}{space 2} .1199789{col 40}{space 1}    1.36{col 49}{space 3}0.173{col 57}{space 4} .9395949{col 70}{space 3} 1.413175
{txt}{space 4}kv_workload {c |}{col 17}{res}{space 2} .9999757{col 29}{space 2} .0000576{col 40}{space 1}   -0.42{col 49}{space 3}0.673{col 57}{space 4} .9998627{col 70}{space 3} 1.000089
{txt}{space 3}polarization {c |}{col 17}{res}{space 2} .0066278{col 29}{space 2} .0152283{col 40}{space 1}   -2.18{col 49}{space 3}0.029{col 57}{space 4} .0000734{col 70}{space 3}  .598574
{txt}{space 7}workload {c |}{col 17}{res}{space 2} 1.002386{col 29}{space 2} .0017399{col 40}{space 1}    1.37{col 49}{space 3}0.170{col 57}{space 4} .9989817{col 70}{space 3} 1.005802
{txt}{space 9}female {c |}{col 17}{res}{space 2} 1.055758{col 29}{space 2} .0925509{col 40}{space 1}    0.62{col 49}{space 3}0.536{col 57}{space 4} .8890899{col 70}{space 3}  1.25367
{txt}{space 3}priorconfirm {c |}{col 17}{res}{space 2}        1{col 29}{txt}  (omitted)
{space 9}denied {c |}{col 17}{res}{space 2} .5621651{col 29}{space 2} .0913423{col 40}{space 1}   -3.54{col 49}{space 3}0.000{col 57}{space 4} .4088445{col 70}{space 3} .7729825
{txt}{space 6}x_itier_2 {c |}{col 17}{res}{space 2} .8292993{col 29}{space 2} .1000082{col 40}{space 1}   -1.55{col 49}{space 3}0.121{col 57}{space 4} .6547293{col 70}{space 3} 1.050415
{txt}{space 6}x_itier_3 {c |}{col 17}{res}{space 2} .5716139{col 29}{space 2}  .111132{col 40}{space 1}   -2.88{col 49}{space 3}0.004{col 57}{space 4} .3904935{col 70}{space 3} .8367422
{txt}{space 6}x_itier_4 {c |}{col 17}{res}{space 2} .6138429{col 29}{space 2}  .069848{col 40}{space 1}   -4.29{col 49}{space 3}0.000{col 57}{space 4} .4911347{col 70}{space 3} .7672093
{txt}{space 8}defense {c |}{col 17}{res}{space 2}  .966303{col 29}{space 2} .1504831{col 40}{space 1}   -0.22{col 49}{space 3}0.826{col 57}{space 4}  .712123{col 70}{space 3} 1.311208
{txt}{space 1}infrastructure {c |}{col 17}{res}{space 2} .8351407{col 29}{space 2} .1382293{col 40}{space 1}   -1.09{col 49}{space 3}0.276{col 57}{space 4} .6037707{col 70}{space 3} 1.155174
{txt}{space 9}social {c |}{col 17}{res}{space 2} .9404328{col 29}{space 2} .1739587{col 40}{space 1}   -0.33{col 49}{space 3}0.740{col 57}{space 4} .6544474{col 70}{space 3}  1.35139
{txt}{space 11}fvra {c |}{col 17}{res}{space 2} 1.057559{col 29}{space 2} .1413376{col 40}{space 1}    0.42{col 49}{space 3}0.675{col 57}{space 4} .8138525{col 70}{space 3} 1.374243
{txt}{space 4}firstrecess {c |}{col 17}{res}{space 2} .9882554{col 29}{space 2} .1150944{col 40}{space 1}   -0.10{col 49}{space 3}0.919{col 57}{space 4} .7865681{col 70}{space 3} 1.241658
{txt}{space 3}secondrecess {c |}{col 17}{res}{space 2} .8406858{col 29}{space 2} .1150647{col 40}{space 1}   -1.27{col 49}{space 3}0.205{col 57}{space 4} .6428797{col 70}{space 3} 1.099355
{txt}policy_majage~y {c |}{col 17}{res}{space 2} 1.119281{col 29}{space 2} .1346648{col 40}{space 1}    0.94{col 49}{space 3}0.349{col 57}{space 4} .8841546{col 70}{space 3} 1.416937
{txt}{space 15} {c |}
{space 8}kbcom_1 {c |}
{space 13}2  {c |}{col 17}{res}{space 2} .6027353{col 29}{space 2} .1016283{col 40}{space 1}   -3.00{col 49}{space 3}0.003{col 57}{space 4} .4331157{col 70}{space 3} .8387822
{txt}{space 13}3  {c |}{col 17}{res}{space 2} .5598151{col 29}{space 2} .0425971{col 40}{space 1}   -7.62{col 49}{space 3}0.000{col 57}{space 4} .4822536{col 70}{space 3} .6498508
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 1.703748{col 29}{space 2} .4745625{col 40}{space 1}    1.91{col 49}{space 3}0.056{col 57}{space 4} .9869871{col 70}{space 3} 2.941029
{txt}{space 13}5  {c |}{col 17}{res}{space 2} .7896578{col 29}{space 2} .1763126{col 40}{space 1}   -1.06{col 49}{space 3}0.290{col 57}{space 4} .5097826{col 70}{space 3} 1.223187
{txt}{space 13}6  {c |}{col 17}{res}{space 2} 1.107272{col 29}{space 2} .2407796{col 40}{space 1}    0.47{col 49}{space 3}0.639{col 57}{space 4}  .723033{col 70}{space 3} 1.695706
{txt}{space 13}7  {c |}{col 17}{res}{space 2} .7601859{col 29}{space 2} .1149419{col 40}{space 1}   -1.81{col 49}{space 3}0.070{col 57}{space 4} .5652181{col 70}{space 3} 1.022406
{txt}{space 13}8  {c |}{col 17}{res}{space 2} .6976441{col 29}{space 2} .2983211{col 40}{space 1}   -0.84{col 49}{space 3}0.400{col 57}{space 4} .3017517{col 70}{space 3} 1.612939
{txt}{space 13}9  {c |}{col 17}{res}{space 2} .4511564{col 29}{space 2} .0642533{col 40}{space 1}   -5.59{col 49}{space 3}0.000{col 57}{space 4} .3412712{col 70}{space 3} .5964233
{txt}{space 12}10  {c |}{col 17}{res}{space 2} .7104577{col 29}{space 2} .1546831{col 40}{space 1}   -1.57{col 49}{space 3}0.116{col 57}{space 4} .4636731{col 70}{space 3} 1.088591
{txt}{space 12}11  {c |}{col 17}{res}{space 2} .7403866{col 29}{space 2} .2761657{col 40}{space 1}   -0.81{col 49}{space 3}0.420{col 57}{space 4} .3564172{col 70}{space 3} 1.538008
{txt}{space 12}12  {c |}{col 17}{res}{space 2} .8163185{col 29}{space 2} .2078848{col 40}{space 1}   -0.80{col 49}{space 3}0.425{col 57}{space 4} .4955546{col 70}{space 3} 1.344707
{txt}{space 12}13  {c |}{col 17}{res}{space 2} .3206445{col 29}{space 2} .0619074{col 40}{space 1}   -5.89{col 49}{space 3}0.000{col 57}{space 4} .2196246{col 70}{space 3} .4681303
{txt}{space 12}14  {c |}{col 17}{res}{space 2} .5901944{col 29}{space 2} .3083584{col 40}{space 1}   -1.01{col 49}{space 3}0.313{col 57}{space 4} .2119671{col 70}{space 3} 1.643318
{txt}{space 12}15  {c |}{col 17}{res}{space 2} .6691059{col 29}{space 2} .2476073{col 40}{space 1}   -1.09{col 49}{space 3}0.278{col 57}{space 4} .3239677{col 70}{space 3} 1.381936
{txt}{space 12}16  {c |}{col 17}{res}{space 2} .6874461{col 29}{space 2} .2044348{col 40}{space 1}   -1.26{col 49}{space 3}0.208{col 57}{space 4} .3838007{col 70}{space 3} 1.231322
{txt}{space 12}17  {c |}{col 17}{res}{space 2} .4433783{col 29}{space 2} .0677327{col 40}{space 1}   -5.32{col 49}{space 3}0.000{col 57}{space 4} .3286553{col 70}{space 3} .5981475
{txt}{space 12}18  {c |}{col 17}{res}{space 2} 1.655029{col 29}{space 2}  .761416{col 40}{space 1}    1.10{col 49}{space 3}0.273{col 57}{space 4} .6717379{col 70}{space 3} 4.077661
{txt}{space 12}19  {c |}{col 17}{res}{space 2} 1.49e-06{col 29}{space 2} 1.56e-06{col 40}{space 1}  -12.75{col 49}{space 3}0.000{col 57}{space 4} 1.89e-07{col 70}{space 3} .0000117
{txt}{space 12}20  {c |}{col 17}{res}{space 2} .4899136{col 29}{space 2} .1159575{col 40}{space 1}   -3.01{col 49}{space 3}0.003{col 57}{space 4} .3080697{col 70}{space 3} .7790944
{txt}{space 15} {c |}
{space 8}presrev {c |}
{space 13}2  {c |}{col 17}{res}{space 2} 2.340786{col 29}{space 2} .6581385{col 40}{space 1}    3.02{col 49}{space 3}0.002{col 57}{space 4} 1.349077{col 70}{space 3} 4.061502
{txt}{space 13}3  {c |}{col 17}{res}{space 2} 1.874494{col 29}{space 2}  .683142{col 40}{space 1}    1.72{col 49}{space 3}0.085{col 57}{space 4} .9176387{col 70}{space 3} 3.829099
{txt}{space 13}4  {c |}{col 17}{res}{space 2} 1.387199{col 29}{space 2} .8730847{col 40}{space 1}    0.52{col 49}{space 3}0.603{col 57}{space 4}  .404021{col 70}{space 3} 4.762925
{txt}{space 13}5  {c |}{col 17}{res}{space 2} 1.219648{col 29}{space 2} .5556938{col 40}{space 1}    0.44{col 49}{space 3}0.663{col 57}{space 4} .4993576{col 70}{space 3}  2.97891
{txt}{space 13}6  {c |}{col 17}{res}{space 2} 1.939045{col 29}{space 2} 1.186051{col 40}{space 1}    1.08{col 49}{space 3}0.279{col 57}{space 4} .5847032{col 70}{space 3} 6.430435
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} 1.033891{col 29}{space 2} 1.878678{col 40}{space 1}    0.02{col 49}{space 3}0.985{col 57}{space 4} .0293603{col 70}{space 3}  36.4073
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}/ln_p {c |}{col 17}{res}{space 2}-.0323359{col 29}{space 2} .0303855{col 40}{space 1}   -1.06{col 49}{space 3}0.287{col 57}{space 4}-.0918903{col 70}{space 3} .0272185
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
              p {c |}{col 17}{res}{space 2} .9681813{col 29}{space 2} .0294186{col 57}{space 4} .9122052{col 70}{space 3} 1.027592
{txt}            1/p {c |}{col 17}{res}{space 2} 1.032864{col 29}{space 2} .0313841{col 57}{space 4} .9731486{col 70}{space 3} 1.096245
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {bf:_cons} estimates baseline hazard{txt}.{p_end}

{com}. *
. 
. * DESCRIPTIVE STATISTICS FOR EACH PARTISAN CONTROL REGIME [NOTE: THESE VARY ACROSS SUBSAMPLES OF INTEREST] *
. sum wSenComm_chair_pres1 if e(sample) & sendivide==0, detail

                    {txt}wSenComm_chair_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}-.7163319      -.7163319
{txt} 5%    {res}-.5463055      -.7163319
{txt}10%    {res}-.5065913      -.7163319       {txt}Obs         {res}        713
{txt}25%    {res}-.4493055      -.7163319       {txt}Sum of wgt. {res}        713

{txt}50%    {res}-.3046792                      {txt}Mean          {res}-.2873832
                        {txt}Largest       Std. dev.     {res} .2103798
{txt}75%    {res}-.1762139       .4892833
{txt}90%    {res}-.0447927       .5914087       {txt}Variance      {res} .0442597
{txt}95%    {res} .1377861       .5914087       {txt}Skewness      {res} 1.295271
{txt}99%    {res} .4892833       .6940686       {txt}Kurtosis      {res} 6.086439
{txt}
{com}. sum wSenComm_chair_pres1 if e(sample) & sendivide==1, detail

                    {txt}wSenComm_chair_pres1
{hline 61}
      Percentiles      Smallest
 1%    {res}-.2693319      -.4493055
{txt} 5%    {res}-.0833319      -.3517167
{txt}10%    {res} .0100685      -.2693319       {txt}Obs         {res}        768
{txt}25%    {res} .1968486      -.2693319       {txt}Sum of wgt. {res}        768

{txt}50%    {res} .3327861                      {txt}Mean          {res} .3084411
                        {txt}Largest       Std. dev.     {res} .2332723
{txt}75%    {res} .4782646       .7534087
{txt}90%    {res} .5828941       .7534087       {txt}Variance      {res} .0544159
{txt}95%    {res} .6940686       .7534087       {txt}Skewness      {res} -.536575
{txt}99%    {res} .6973208       .7534087       {txt}Kurtosis      {res} 3.100178
{txt}
{com}. 
. 
. ** CONDITIONAL COEFFICIENT ANALYSIS TESTS: DIRECTION [+] ** 
. 
. * DIFFERENCE BETWEEN DIVIDED AND UNIFIED PARTISAN CONTROL OF SENATE & PRESIDENCY: INTERQUARTILE UNIT CHANGE IN "wSenComm_chair_pres1"  *
. lincomest (chair_pres1 * 0.2730916 +  1.sendivide#c.chair_pres1 * 0.281416) - chair_pres1 * 0.2730916, eform(hr)
{txt}Confidence interval for formula:
{res}(chair_pres1*0.2730916+1.sendivide#c.chair_pres1*0.281416)-chair_pres1*0.2730916

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} 1.206169{col 26}{space 2} .1516174{col 37}{space 1}    1.49{col 46}{space 3}0.136{col 54}{space 4} .9427809{col 67}{space 3} 1.543141
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix model4b = r(table)
{txt}
{com}. mat list model4b
{res}
{txt}model4b[9,1]
               (1)
     b {res} 1.2061691
{txt}    se {res} .15161742
{txt}     z {res} 1.4912244
{txt}pvalue {res} .13590259
{txt}    ll {res} .94278093
{txt}    ul {res} 1.5431411
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         1
{reset}
{com}. 
. 
. 
. 
. 
. *** CREATE FIGURE G1 BASED ON MODELS 1A/1B/2A/2B/3A/3B/4A/4B ****
. 
. **** FIGURE G1 ****
. 
. matrix A = J(8, 3, .)
{txt}
{com}. matrix coln A = Point ll95 ul95
{txt}
{com}. matrix rown A = 1 2 3 4 5 6 7 8
{txt}
{com}. 
. matrix A[1,1] = model1a[1,1]
{txt}
{com}. matrix A[1,2] = model1a[5,1]
{txt}
{com}. matrix A[1,3] = model1a[6,1]
{txt}
{com}. 
. matrix A[2,1] = model1b[1,1]
{txt}
{com}. matrix A[2,2] = model1b[5,1]
{txt}
{com}. matrix A[2,3] = model1b[6,1]
{txt}
{com}. 
. matrix A[3,1] = model2a[1,1]
{txt}
{com}. matrix A[3,2] = model2a[5,1]
{txt}
{com}. matrix A[3,3] = model2a[6,1]
{txt}
{com}. 
. matrix A[4,1] = model2b[1,1]
{txt}
{com}. matrix A[4,2] = model2b[5,1]
{txt}
{com}. matrix A[4,3] = model2b[6,1]
{txt}
{com}. 
. matrix A[5,1] = model3a[1,1]
{txt}
{com}. matrix A[5,2] = model3a[5,1]
{txt}
{com}. matrix A[5,3] = model3a[6,1]
{txt}
{com}. 
. matrix A[6,1] = model3b[1,1]
{txt}
{com}. matrix A[6,2] = model3b[5,1]
{txt}
{com}. matrix A[6,3] = model3b[6,1]
{txt}
{com}. 
. matrix A[7,1] = model4a[1,1]
{txt}
{com}. matrix A[7,2] = model4a[5,1]
{txt}
{com}. matrix A[7,3] = model4a[6,1]
{txt}
{com}. 
. matrix A[8,1] = model4b[1,1]
{txt}
{com}. matrix A[8,2] = model4b[5,1]
{txt}
{com}. matrix A[8,3] = model4b[6,1]
{txt}
{com}. 
. 
. 
. coefplot (matrix(A[,1]), ci((2 3))), grid(none) xline(1, lcolor(red%40) lpattern(dash)) xtitle("Hazard Ratio", size(small) margin(t=2)) ylabel(1 "Model G1.A" 2 "Model G1.B" 3 "Model G2.A" 4 "Model G2.B" 5 "Model G3.A" 6 "Model G3.B" 7 "Model G4.A" 8 "Model G4.B", labsize(small) noticks) mlabel format(%9.3f) mlabposition(12) mlabsize(vsmall) xlabel(0(1)3, angle(0) labsize(small) format(%9.1f)) msymbol(o) mcolor(black) msize(vsmall) title("FIGURE G1", size(med)) ciopts(lcolor(black)) legend(off) subtitle("Differential Partisan Control Effects of Committee-President Ideological Distance" "(Distinctions Between Nominees With and Without Prior Senate Confirmation)", size(small))
{res}{p 0 4 2}
{txt}(note:  named style
med not found in class
gsize,  default attributes used)
{p_end}
{res}{txt}
{com}. 
. *graph save "Graph" "C:\Users\gk57526\Dropbox\Confirmation Dynamics Project (Jason Byers)\Confirmation Delay & Senate Committees\2023 Version\Fall 2024\Statistics\Graphics\FigureH1.gph", replace
. 
. graph save "Graph" "/Users/jasonbyers/Dropbox/Jason Byers/Co-Authored Projects/Projects with George Krause/Krause Projects/Confirmation Dynamics Project/Confirmation Delay & Senate Committees/2023 Version/Fall 2024/Statistics/Graphics/Appendix G/FigureG1.gph", replace
{res}{txt}file {bf:/Users/jasonbyers/Dropbox/Jason Byers/Co-Authored Projects/Projects with George Krause/Krause Projects/Confirmation Dynamics Project/Confirmation Delay & Senate Committees/2023 Version/Fall 2024/Statistics/Graphics/Appendix G/FigureG1.gph} saved

{com}. 
. 
. 
. 
. 
. 
. 
. 
. 
. ********************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. log close 
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}/Users/jasonbyers/Dropbox/Jason Byers/Co-Authored Projects/Projects with George Krause/Krause Projects/Confirmation Dynamics Project/Confirmation Delay & Senate Committees/2023 Version/Fall 2024/Statistics/Output/Committee Delay.APPENDIX G RESULTS.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}25 Dec 2024, 22:01:21
{txt}{.-}
{smcl}
{txt}{sf}{ul off}